Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
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RULE BASED DATA COLLECTION AND MANAGEMENT IN
A WIRELESS COMMiJNICATIONS NETWORK
BACKGROUND OF THE INVENTION
Field of the Invention
The present invention relates generally to wireless communications networks
and
related systems and devices. More particularly, exemplary embodiments of the
invention
concern systems and methods for using distributed network elements to
implement
monitoring and data collection concerning selected network parameters.
Related Technology
As a result of advances in technology and enormous increases in the number of
wireless device users, the size and complexity of wireless communications
networks has
greatly increased. An inevitable consequence of such increases in size and
complexity
has been a relative increase in operational and performance problems
associated with
communications networks. Reliability issues, such as dropped calls, lack of
coverage,
2o and poor audio quality are impeding the acceptance of wireless technology
by end users.
These and other quality issues have prevented many end users from relying upon
wireless
voice and data services as their primary means of communication. As new
services are
introduced that use even more complex technology, exercise different usage
modalities,
and place additional demands on networks already laden with problems, network
performance will deteriorate further. Quality of service has a direct impact
on customer
churn, a tough and costly problem that reduces profitability. Therefore,
improving quality
of service is a top priority for service providers.
Network monitoring solutions are well known in the art and widely employed by
service providers, however, currently available solutions can only monitor and
diagnose
subsets of the overall telecommunications system and therefore do not provide
the holistic
view of network and device performance needed to efficiently identify and
resolve quality
issues. Typical approaches to network monitoring include "self-monitoring"
wherein a
network element reports on its own status and performance and reports any
errors that
occur during its operation. The resulting operational metrics from a single
element can
sometimes be indicative of a broader, system-wide problem, but rather than
providing
answers, problem resolution entails guesswork and extended troubleshooting,
which
wastes valuable resources. Another common approach includes placing probes at
various points in the network to determine if network elements are functioning
according
to specification. Sometimes referred to as "sniffers", "log monitors" or
"event monitors",
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these monitoring systems are effective at identifying performance issues with
a particular
network element, but they fail to capture problems that stem from the
interfaces among
network elements, i.e., these solutions do not address the case where single
elements are
performing according to specifications, but problems occur when those elements
interact
with one another. This far more complex and subtle set of problems has costly
consequences to network operators when services cannot be delivered to end
customers.
Another monitoring approach known in the art involves pre-programmed service
monitors, where specific elements perform service transactions to emulate
"real-world"
transaction activity; end to end performance is then monitored and the results
reported.
While these solutions catch systematic failures, they cannot detect
intermittent or
dispersed problems, subtle impairments, or device or end user specific issues.
Further,
they can only test anticipated usage scenarios and fail to adapt to new usages
and
interactions between services.
Significantly, the aforementioned solutions lack the ability to monitor
network
conditions and intelligently and dynamically define and generate data
collection models
in response to changing network conditions. Even with the employment of probes
in a
communications network, it is often the case that the probe provides only an
indication of
a problem, and actually troubleshooting the problem requires personnel to be
dispatched
to a physical location on the network, adding significant time and cost to
problem
identification and resolution. Moreover, these troubleshooting techniques do
not provide
a multi-faceted view of the different network layers, such as the physical
layer, the
applications layer, etc., and they do not correlate performance issues across
these layers.
As a result, numerous quality issues impacting end users go undetected or are
misunderstood. Consequently, they may become crises because the performance
data
provided by currently available network monitoring solutions lacks the detail
and
timeliness needed to quickly identify, prioritize and resolve network issues.
Furthermore, currently available network monitoring solutions cannot
adequately
monitor and report on a particular end user's experience with network usage,
therefore,
service providers must rely upon the end user to report performance problems
to a
customer service representative. However, it is frequently the case that once
reported, an
end user's problem cannot be duplicated due to the difficulty of recounting
the details of
what s/he experienced, the timing of the occurrence, and the lack of
underlying data to
validate the issue. Additionally, because the service provider is unable to
view network
performance holistically, it likely does not understand the true scope of the
reported
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problem and it cannot appropriately prioritize the problem for resolution. The
problem,
therefore, is not resolved to the reporting end user's satisfaction, creating
a disincentive
for the end user to diligently report problems in the future. Furthermore, an
opportunity
to prevent the issue from affecting others and to improve the overall quality
of the
network is missed.
Thus, situations frequently arise where the end user is alienated from the
company
providing the communications service, without the service provider even being
aware of
the cause or source of the end user's dissatisfaction. Moreover, because so
many end user
problems go unreported, it is almost impossible for service providers to
obtain reliable
information about the scope of a particular issue. Therefore resources are
frequently
spent solving issues that are well described, but only affect a small number
of end users,
versus problems that are poorly described but effect a much larger number of
end users.
As a result, a service provider with an incorrect understanding of the scope
of an issue
may allocate an inappropriate aniount of resources toward resolution, or it
may fail to
recognize the value of prioritizing resolution.
Still other monitoring solutions known in the art are directed to gathering
and
analyzing information about the performance of wireless devices. Typically,
the
monitoring software will be installed on a wireless device at the time of
manufacture or
by downloading the software onto the device. The software then runs
continuously in the
background, monitoring device and application performance. When a particular
event or
error associated with the device occurs, the software collects the data
associated with the
error or event and may upload it either in real time or at a later time to a
data repository
for analysis. As discussed below however, such approaches are inflexible and
fall well
short of an adequate or effective solution.
Just as the aforementioned network monitoring solutions monitor the
performance of particular elemeiits in the network, the wireless device
monitoring
software contributes another set of data points concerning the performance of
the wireless
device, but the fundamental problem remains that while device performance
information
is useful, it is disconnected from the other performance data being generated
elsewhere in
the network, and there is no mechanism for understanding this data in the
context of the
performance of multiple network elements across network layers.
Furthermore, such approaches tend to emphasize the use of pre-configured data
gathering software. While the software can be instructed to collect certain
subsets of data,
the software cannot be quickly revised or modified to accommodate rapidly
emerging and
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changing conditions. That is, the software can only collect the data that was
originally
programmed to be collected and further, such data can only be collected in
accordance
with the conditions initially programmed. Thus, the capabilities of such
software are
constrained by the foresight of the programmer. Because it is simply not
possible for a
programmer to be able to anticipate the wide variety of usage conditions,
problems and
events that may occur in connection with communications network operations,
this lack
of flexibility is a significant limitation.
This lack of flexibility is also problematic in situations where a transient
network
condition occurs. In particular, because the software cannot be quickly and
easily
updated to respond to changing network conditions, the window of opportunity
to collect
data concerning a transient network condition may close before the software
can be
modified to target that data, thus denying network administrators and other
personnel the
opportunity to adequately diagnose and resolve the problem.
Finally, the flexibility of such software is further impaired by the fact that
such
software is either loaded on the mobile phone at the time of manufacture, or
must be
downloaded from a web site or service. Thus, revisions or updates to the data
gathering
software are somewhat cumbersome and time-consuming to obtain. Because
different
users may load the revised software, if at all, at different times, there is
no quick and
reliable way to ensure that a statistically significant number of devices are
available, with
the appropriate software, to gather the data needed for a particular analysis.
BRIEF SUMMARY OF AN EXEMPLARY EMBODIMENT OF THE INVENTION
In view of the foregoing, and other problems in the art, the present invention
relates to systems and methods that implement a new way to monitor services in
a
wireless communications network by utilizing the numerous "end points" or end
user
devices to capture "real world" usage and performance data across network
elements and
layers. Because many errors that occur in conjunction with the performance of
certain
services are only visible from the perspective of the end user's wireless
device, the
methods of the present invention enable the collection of this data which
would otherwise
be unavailable. Further, the data collection methods disclosed herein allow
interactions
within and among multiple network layers and network elements to be identified
and
accurately associated with one another. In this manner, valuable diagnostic
data
corresponding to the performance of services within the context of conditions
occurring
among multiple layers of the network, including the physical layer, the
transport layer,
and the application layer, can be viewed and analyzed.
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While data collection methods are already in use in connection witli large
numbers
of high capacity end points such as networked PCs and with singular, highly
specialized
systems with considerable constraints such as the Mars lander system, the
methods
disclosed herein are directed to service monitoring techniques that rely on a
vast number
of wireless devices with relatively limited functionality (e.g. constrained
memory
capacity and battery life) and complex dependencies (e.g. interaction with RF
networks
providing variable, capacity and reliability) to monitor and capture network
and device
performance data in response to changing network conditions. These conditions
are often
transient, geographically isolated, and/or dependent on specific interactions
between
network elements. Thus, the data collection and management system of the
present
invention addresses a very different set of problems than those addressed by
data
collection systems known in the art.
Exemplary embodiments of the systems and methods of the invention can be
implemented by selecting and using distributed wireless devices, wireless
telephones and
telephony-enabled personal digital assistants (PDAs), to implement monitoring
of one or
more wireless communications network parameters, collection of data concerning
such
parameters, and conditional transmission of collected data to a reporting
system. In
conjunction with the monitoring and data collection activity of wireless
devices, it should
be noted that in some embodiments, the methods of the invention may be
implemented
using network nodes other than wireless devices, including wireline devices,
application
servers or other servers on the network, where data can be collected and then
processed as
described above.
One embodiment of the invention provides for a service quality platform of the
data collection and management system to dynamically generate and download to
a
population of wireless devices rule-based data collection profiles. Data
collection profiles
may be generated manually by a network administrator, a software developer or
other
personnel involved in the operation of the network (hereinafter referred to as
"network
administrators"), created offline as a portion of a data analysis solution, or
automatically
generated based on network parameters or other events. Profiles define what
infonnation
is to be collected on the devices in response to which conditions and events,
as well as the
conditions and events that cause the device to upload the collected
information.
Conditions or events include any occurrence in the network or on the device
that the
device can sense, such as a call dropping or a user pressing a button on the
device.
Conditions and events also include the passage of time, or a request from a
network
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administrator that the device report information back to the server. In the
exemplary
embodiment, a population of wireless devices (which may be referred to herein
as
"wireless device(s)","wireless communication device(s)", target wireless
device(s)", or
"the device(s)") that is to receive the data collection profile and execute
data collection is
selected based on the characteristics, capacity, and availability of an end
user's wireless
device. As part of the target wireless device qualification and selection
process,
particular attention is directed to implementing the collection of data in
such a way as to
avoid overwhelming end user devices. Similarly, when defining the data
collection rules
in the data collection profile, consideration is given to the impact on device
and network
resources of the desired data collection activity, and the rules defining
profile download,
data collection, and upload of collected data are defined in such a way as to
avoid
adversely impacting network performance. For example, in some cases, uploading
collected data may occur only in off-peak times when device and network
activity is
particularly low. Furthermore, because network monitoring and data collection
activity is
expensive in terms of the device and network resources utilized, in addition
to the
rigorous device qualification process, methods of the invention provide the
ability to
structure a data collection profile to ensure that extraneous data is filtered
during the data
collection process and that only the most relevant and reliable data is
presented for
analysis with regard to a particular issue.
The invention may be practiced in conjunction with a wireless communications
network such as a wireless cellular telephone network that includes a
plurality of wireless
devices, such as wireless telephones that are suitably equipped to establish a
connection
to and communicate with the network. The data collection and management system
is
comprised of the service quality platform (SQP), which generates and manages
data
collection activities and processes and stores collected data, and the service
quality client
(SQC), which resides on the target wireless device or another target network
node to
enable it to participate in data collection activities.
In operation, the data collection and management system of the invention
enables
a multitude of wireless devices and network nodes, each equipped with an SQC,
to
provide information regarding complex network status issues. The following
discussion
presents an exemplary embodiment of the invention in which queries are used to
obtain
such information, although the invention is not limited to the following mode
of
operation. According to this embodiment, a complex network status issue can be
described in terms of a "query"; i.e. a question regarding the status or
performance of a
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network device or other aspects of network performance. In response to
initiation of such
a query, the SQP determines if it already has data stored within one of its
subsystems that
meets the criteria specified in the query; if so, that data is made available
for analysis and
the query is answered immediately. If the required data does not already exist
in the SQP,
a collection task request (CTR) is generated and processed by the tasking sub-
system of
1o the SQP. CTRs are typically defined in advance as part of a data collection
and analysis
package that addresses a particular business or technical need. The CTR is
then stored in
the SQP, and invoked as the need arises. In some cases, the CTR can be defined
on
demand by a network administrator. The CTR is then used as a basis for
building a data
collection profile. The profile describes for each target wireless device that
receives it
what parameters should be captured, and what events will cause data to be
captured,
stored, and uploaded. Once a data collection profile has been created, a set
of target
wireless devices is selected based upon criteria relating to the CTR and to
the
characteristics of the available wireless devices. Qualifying characteristics
may include
device type, such as manufacturer and model, available memory and battery
life, the type
of applications resident on the device, the geographical location of the
device, usage
statistics, including those that characterize a user's interaction with a
device, and the
profile of the customer. The data collection profile is then provided to the
SQC on the
target wireless devices.
As noted previously, in some embodiments data collection profiles are also
sent to
other network nodes, such as an application server. It should be noted that
use of the term
"target devices" herein refers to a broader category of devices that includes
wireless
devices and other network nodes that may be employed by SQP in the collection
of data.
In accordance with the instructions specified in the profile, the SQC on the
target devices
and other network nodes collects, stores, packages and uploads the specified
data.
Finally, the SQP receives the reported data and processes it to provide useful
information
for decision support. Based on the reported data, additional queries and data
collection
profiles may be generated and executed to further explore and diagnose a
problem. For
example, based on a set of rules, additional queries may be automatically
generated,
target wireless devices may be automatically selected, and the new queries,
encompassed
in a data collection profile, can be sent to the selected devices. In other
situations, the
existing data collection profile may persist on a device for any amount of
time and direct
the SQC to continue to periodically collect, package, and upload data. More
generally, the
data collection profile may be deactivated, refined, or replaced at any time.
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These and other aspects of embodiments of the present invention will become
more fully apparent from the following description and appended claims.
IEF DESCRIPTION OF THE DRAWINGS
In order that the manner in wliich the above-recited and other advantages and
features of the invention are obtained, a more particular description of the
invention
1o briefly described above will be rendered by reference to specific
embodiments thereof
which are illustrated in the appended drawings. Understanding that these
drawings depict
only typical embodiments of the invention and are not therefore to be
considered limiting
of its scope, the invention will be described and explained with additional
specificity and
detail through the use of the accompanying drawings in which:
Figure 1 illustrates an example of a wireless communications network in which
the data collection system may be practiced
Figure 2 is a schematic view illustrating aspects of a data collection and
management system suitable for use in connection with communications network
operations;
Figure 3 is a schematic view depicting various considerations that relate to a
query
that can be executed by the data collection and management system;
Figure 4 is a schematic view of a data collection profile that may be employed
by
embodiments of the data collection and management system;
Figure 5 is a flow diagram illustrating aspects of an exemplary process for
formulating and rendering a query;
Figure 6 is a flow diagram illustrating aspects of an exemplary process for
generating a data collection profile;
Figure 7 is a flow diagram illustrating aspects of an exemplary process for
collecting data in connection with a data collection profile; and
Figure 8 is a flow diagram illustrating aspects of an exemplary process for
using
data collected in connection with a data collection profile.
Figure 9 is a flow diagram depicting an exemplary process for triggers
activating
data collection activities
Figure 10 depicts an exemplary process for invoking a domino trigger
DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION
Reference will now be made to the drawings to describe various aspects of
exemplary embodiments of the invention. It should be understood that the
drawings are
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diagrammatic and schematic representations of such embodiinents and,
accordingly, are
not limiting of the scope of the present invention, nor are the drawings
necessarily drawn
to scale.
Embodiments of the invention relate to systems and methods for using
distributed
wireless devices and other network nodes to implement monitoring and data
collection
concerning selected communications network parameters. The collected data can
then be
analyzed and data collection efforts further focused and refined as suggested
by the
collected data and associated trends. The data analyses may be used in
connection with,
among other things, detecting network impairments and outages, implementation
of
corrective actions, streamlining of network operations, improvements to
customer service,
and development of marketing strategies.
I. Exemplary Wireless Communications Network and Wireless Devices
In order to describe the various methods of the invention, Figure 1
illustrates an
example of a wireless network 100 in which the invention can be practiced. It
should be
understood, of course, that this and other arrangements and processes
described herein are
set forth for purposes of example only, and other arrangements and elements
(e.g.,
machines, interfaces, functions, orders of elements, etc.) can be added or
used instead and
some elements may be omitted altogether. Further, those skilled in the art
will appreciate
that many of the elements described herein are functional entities that may be
iinplemented as discrete components or in conjunction with other components,
in any
suitable combination and location, and by software, firmware and/or hardware.
The network of Figure 1 represents only an example of the suitable
environments
in which the invention can be implemented, and other network architectures are
possible.
In particular, wireless network 100 is described and illustrated as a Code
Division
Multiple Access (CDMA) network, whereas the invention can be practiced with
other
wireless networks, includ.ing Global System for Mobile Communications (GS1VI),
Universal Mobile Telecommunications System (UMTS), Time Division Multiple
Access
(TDMA), Wideband Code Division Multiple Access (WCDMA), General Packet Radio
Service (GPRS) networks, 802.11 networks and other networks, including those
that will
be developed in the future. More specifically, in the exemplary embodiment of
the
invention, wireless network 100 includes a radio frequency (RF) network that
provides
radio connectivity and session management for circuit-switched and packet data
technology-based communication. Accordingly, wireless network 100 includes or
interfaces with all of the elements necessary to route circuit-switched
telephone calls
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and/or packet data communication through the network, including one or more
wireless
devices 400, a base station 120, base station controller (BSC) 130, mobile
switching
center (MSC) 150 and a packet data serving node (PDSN) 140. More specifically,
the
methods of the invention can be used in conjunction with a circuit-switched
network, a
packet data network, or both. While the exemplary embodiment of the invention
uses
Internet Protocol (IP) as its transport protocol, the methods of the invention
may be
implemented using other transport protocols, such as short message service
(SMS) and
Short Data Burst services that are well known in the art. Wireless network 100
may also
include a Home Location Register (HLR), Visiting Location Register (VLR),
billing and
provisioning systems, one or more gateways, the servers and infrastructure
necessary to
use short message service messages, and may include many other network
elements not
depicted in Figure 1. Application servers or third party reporting systems
(depicted as
network server 102 in the exemplary embodiment), may reside outside network
100 and
can be used in conjunction with the present invention. References herein to
the terms
"wireless network" or "the network" throughout should be construed as
inclusive of the
network infrastructure, servers, end user devices, and applications and
services.
Wireless network 100 may further include third party network monitors, probes,
and packet sniffers, which are known in the art, for use in conjunction with
the present
invention. Data collection and management system 200, while depicted for
purposes of
illustration as functioning in conjunction with the packet data network, may
receive data
from nodes on a circuit-switched network or elements of the system may be
located in a
circuit-switched network and receive data from a packet data network.
Gateways,
network monitors and other network elements may be employed to facilitate
transmission
of data between the networks and the data collection and management system
200.
Furthermore, in one embodiment, elements of data collection and management
system
200 may be implemented on otie or more network servers residing within the
network
operator's network. Alternatively, data collection and management system 200
may be
implemented as a service hosted by a service provider other than the network
operator,
and elements of the system may therefore reside outside the network operator's
network
and be equipped to communicate with the various nodes in the network
operator's
network.
II. Structure of Exemplary Data Collection and Management System
Figure 2 illustrates details concerning an implementation of a data collection
and
management system, denoted generally at 200, as well as some of the related
components
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of wireless network 100 with which it can be used. The functionality disclosed
herein
may be employed in connection with a wide variety of network devices, either
wireless or
wireline, including radios, personal digital assistants ("PDA"), network
servers, desktop
computers and other devices associated with network communication.
In the exemplary embodiment, the data collection and management system 200 of
lo Figure 2 makes use of one or more target wireless devices 400 that enable
an end user to
gain access to telephony services and is equipped to provide access to
Internet or
multimedia data through any suitable protocol that allows target wireless
device 400 to
participate in a packet data network. Target wireless device 400 can be
substantially any
mobile wireless device that can communicate in the environment of wireless
network
100, and can be a wireless telephone handset, a wireless personal digital
assistant (PDA),
or another wireless communication device. The wireless devices can also be
referred to
as mobile stations, or mobile devices, and hereinafter will be referred to as
wireless
devices.
Target wireless device 400 has a local memory that is used to locally store
data
that is transmitted over wireless network 100 and permits the execution of
software such
as an operating system and applications, and to otherwise support the
operation of the
wireless station. A variety of operating systems known in the art such as
Symbian, REX,
or any other suitable operating system may reside on the wireless device. In
addition,
target wireless device 400 is enabled witli service quality client software
(SQC) 402 that
allows it to participate in data collection activities by receiving and
executing data
collection profiles and otherwise communicating with service quality platform
(SQP) 201
of data collection and management system 200. SQC 402 may be installed on the
wireless device by a variety of methods, including installation at the time of
manufacture,
various download methods such as placing the device in a cradle which is
connected via a
cable to a computer, or using any number of over-the-air riiethods.
Development environments such as BREW and JAVA may also reside on the
wireless device and support such downloads of SQC software 402 or otherwise
support
operation of the data collection system. Further, a typical target wireless
device 400
includes a variety of application software that enables the wireless device to
access one or
more services offered by the network service provider or which provide utility
or
entertainment for the user such as calculators and games. Typical target
wireless devices
400 also include a radio transmitter and receiver, circuits for voice encoding
and decoding
and for call control, a display device, a keyboard, a power supply and may
include a
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Subscriber Identity Module (SIM) chip. It should be noted that in other
embodiments,
SQC software 402 may also be installed on other nodes in the network in order
to receive
and execute data collection profiles as previously noted. For example, in
addition to the
data collection activities of the wireless devices, the SQC software may be
installed on an
application server within the network or on the PDSN so these network nodes
may
participate in the data collection activity.
With continuing reference to Figure 2, data collection and management system
200 includes SQP 201 and SQC 402. Elements of SQP 201 include metrics
collection
sub-system (MCS) 202, coniposed of metrics collector 202A and metrics analyzer
202B;
tasking sub-system 204 composed of tasking processor 204A, tasking database
204B and
target device database 204C; the profile sub-system 206 composed of profile
builder
206A, profile editor 206B and profile database 206C; reporting sub-system 208
composed
of reporting engine 208A, rules engine 208B and reporting database 210; and
interface
sub-system 212 composed of the user interface (UI) 212A and API/services
interface
212B. Data collection and management system 200 further encompasses one or
more
target wireless devices 400 or other network nodes on which resides SQC 402.
Additionally, data collection and management system 200 may communicate with
one or
more network servers 102, such as a third party reporting system.
As noted earlier, the data collection and management system 200 of Figure 2
may
be implemented as a service hosted by a service provider other than the
network operator
or, in other implementations some or all of the functionality of the data
collection and
management system 200 may be provided in the form of a stand- alone software
package
suitable for installation on a network server and/or other network systems
within the
network operator's wireless network 100. Accordingly, the scope of the
invention should
not be construed to be limited to any particular form of implementation of the
data
collection and management system 200. -
The SQP 201 of data collection and management system 200 generally serves to
create and manage various queries, CTRs and to generate data collection
profiles as may
be employed in the collection of data. Further, SQP 201 receives collected
data and
performs various analyses and other processes concerning the collected data.
With continuing reference to SQP 201 of Figure 2, metrics collector 202A of
MCS 202 receives collected data from a plurality of wireless devices 400 or
other
network entities. The collected data may be provided to metrics collector 202A
either
directly or via other network nodes such as PDSN 140 or gateway 160. The MCS
202
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may communicate with tasking sub-system 204 and reporting sub-system 208. The
metrics analyzer 202B may perform validation, augmentation and/or analysis
functions
such as incident matching of the received data prior to passing it on to the
other sub-
systems of SQP 201. The MCS 202 may also receive and respond to requests for
collection profiles from SQC 402 enabled devices. For example, upon initial
activation of
a device enabled with SQC 402, the SQC indicates its presence to SQP 201 via
MCS 202,
in response to which one or more profiles may be downloaded to the device.
Reporting sub-system 208 stores reports generated as a result of inputs from
MCS
202, and data from external systems such as third party network monitors, in
reporting
database 208C. The reporting database 208C may also export or publish report
data to
another reporting or presentation system, depicted in the exemplary embodiment
as
network server 102. Reporting database 208C may be integrated with data
collection and
management system 200 or another network element, or it may function as a
standalone
database. The reporting sub-system 208 further performs a central role in the
collection
tasking process as described below.
In one embodiment of the invention, the information regarding complex network
status issues can be obtained using the following procedures, although the
invention is not
limited to the following mode of operation. According to this embodiment, when
processing a new query, reporting sub-system 208 first checks if reporting
database 208C
already has data that is sufficient and necessary to answer the query. If it
does, and no
additional collection is required to satisfy the query, the data and/or
reports are returned
to the network administrator. If the reporting database 208C does not contain
data to
answer the query, a CTR is generated and tracked throughout its lifecycle by
reporting
sub-system 208 and processed by the tasking sub-system 204. Tasking sub-system
204
communicates with profile sub-system 206 to select an existing data collection
profile or
generate a new data collectioh profile as needed, identify the appropriate set
of targef
wireless devices, send the data collection profile to the selected target
wireless devices,
and communicate with the reporting sub-system to keep track of the collection
task and
original query. If the query requires collection from a non-SQP device, i.e. a
device that
has not been enabled with an SQC to allow it to participate in data collection
and
management system 200, the reporting sub-system 208 will generate and send a
CTR for
the external system through the interface sub-system 212. This way, a required
task, while
not directed by data collection and management system 200, can be documented,
tracked,
and viewed within the system and within the context of other data collection
activities
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being -conducted by the system. It should be noted that tasking sub-system 204
and/or
reporting sub-system 208 may also consider the priority of the query and/or
CTR when
generating data collection profiles and identifying the target device
population. It is also
noted that any of the foregoing tasking functions can be replaced by an
operator and,
according to another embodiment of the invention, the operator directly
assigns profiles
to devices.
SQP 201 may communicate with one or more network servers 102 to provide data
collection and management services. For example, reporting subsystem 208 of
SQP 201
can provide reports, raw data and other data products to network servers 102.
Network
administrators and external systems can then access the data by way of network
server
102. Elements of data collection and management system 200 may also
communicate
with various messaging services in wireless network 100 such as a short
message service
center (SMSC) 180 to initiate communication with one or more target wireless
devices
400 or to notify network administrators that requested data has been collected
and is
available for analysis.
SQP 201 further includes a profile sub-system 206 which cooperates with
tasking
subsystem 204, rules engine 208B and target device database 204C to generate
or modify
various data collection profiles that govem the collection of data concerning
various
network operations and parameters. To this end, profile sub-system 206
includes profile
builder 206A, profile editor 206B, and profile database 206C. Note that
profile sub-
system 206 may be configured and implemented in various ways. In one
implementation,
profile sub-system 206 comprises an element of SQP 201. In another
implementation,
profile sub-system 206 is a stand alone system configured to communicate with
data
collection and management system 200. Accordingly, the scope of the invention
should
not be construed to the implementation of the profile sub-system 206 indicated
in Figure
2.
The data collection profiles generated in connection with profile sub-system
206
can then be downloaded to a designated set of target wireless devices 400.
Tools can also
be used at this point to identify target devices that are compatible with the
profile and
suitable for the query. SQC 402 that is resident on target wireless device 400
receives
data collection profiles and executes data capture processes in response to
"triggers"
defined in the profile, which initiate and terminate data collection
activities, as well as in
response to other rules and instructions in the data collection profiles. Data
collection
rules, triggers, and other instructions contained in data collection profiles
are sometimes
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referred to herein collectively as "data collection directives" as a matter of
convenience.
As suggested earlier, the target wireless device 400 can be a mobile phone or
other
wireless device. However, as mentioned previously, a target device may be any
other
network'element or node that is equipped with SQC software, allowing it to
collect and
upload data to SQP 201.
Data collected by target wireless devices 400 may be buffered in SQC 402
awaiting creation of a metrics package. Once created, a metrics package may be
archived
in the metrics archive of SQC 402, deleted, or uploaded to metrics collector
202A of
MCS 202.
UI 212A of interface subsystem 212 can be a graphical user interface that
enables
one or more network administrators, to interact with and control the operation
of data
collection and management system 200. In this regard, it should be noted that
in at least
some implementations of data collection and management system 200, UI 212A
facilitates generation and manipulation of queries, discussed below, by a
network
administrator concerning collection of data relating to one or more aspects of
the wireless
network 100. In some cases, such queries may be automatically created or
refined based
on reports generated and output by reporting sub-system 208 or as the result
of processing
by rules engine 208B. Additionally, UI 212A may be used by network
administrators to
retrieve data and reports from the system and the API/services interface 212B
may be
used by external systems to submit commands and requests to the system and to
retrieve
reports and data generated from the data collection and management system 200.
Finally, the target device database 204C includes a variety of types of
information
pertaining to target wireless devices, such as mobile telephones, and other
network nodes
that comprise elements of the wireless network 100. Target device database
204C may be
implemented in many different manners. It may be an existing network element
in the
service provider's network such as a Home Location kegister (HLR), in which
information about the characteristics and behavior of wireless devices is
stored and
accessed by elements of the data collection and management system 200.
Alternatively,
target device database 204C may reside within the data collection and
management
system 200 wherein it collects device usage information and device
characteristics upon
the device registering witli wireless network 100. In some cases, a data
collection profile
specifically directed to gathering information to populate the target device
database can
reside on the wireless device, gather status and usage information about the
device such
as applications used, base stations encountered, etc... and then report this
information to
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the target device database 204C. By providing such data and periodic updates
to target
device database 204C, SQP 201 can finely tune its device selection criteria
for more
effective device targeting. In many cases, the target device database will
make use of data
from multiple sources, including HLR data, data generated by profiles, and
data from
other databases associated with user accounts, device properties, or network
characteristics amongst others. As a result, data collection profiles are
downloaded to
those target wireless devices 400 that are best suited for collection of the
data that is
responsive to the defined query or queries. It should be noted that the
interfaces to the
aforementioned multiple sources are well known in the art, and therefore not
described
herein.
Accordingly, the target device database 204C can include information such as
the
model number and manufacturer of the target wireless device, the account type
or types
associated with the target wireless device, information concerning specific
hardware
features of the target wireless device such as the battery type and memory
size, the billing
address associated with the target wireless device, usage information,
applications
installed, geographical areas frequented, and any other information that
facilitates
selection of one or more target wireless devices 400 in connection with a
particular query
concerning the communications network. The database can be created from
information
collected from the devices themselves via the data collection and management
system or
by any other suitable means. In addition, it is noted that the foregoing are
exemplary only
and, more generally, virtually any other target wireless device
characteristics that are
desired to be employed or considered to be relevant may be included in the
target device
database 204C.
Additionally, because data collection and management system 200 allows
multiple
data collection profiles and data analysis activities to be performed
simultaneously, a
particular device may be targeted to execute multiple data collection
profiles. Therefore,
target device database 204C tracks the data collection activity occurring on
the devices
and maintains detailed information about the specific data collection profiles
that are
active on the devices. In doing so it can detect and resolve any contention or
prioritization
issues by adjusting the population of target devices selected.
Target device database 204C may also store information about non-SQP entities
in the network, including characteristics such as location of the non-SQP
device in the
wireless network 100, geographical areas serviced, data available etc... In
general,
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virtually any other characteristic or attribute of the non-SQP entity that
could be
considered relevant may be stored.
Finally, it should be noted that Figure 2 illustrates one manner in which
various
functionalities associated with the data collection management system 200 may
be
allocated. Accordingly, the functionalities disclosed herein in connection
with the data
collection and management system 200 may be allocated in a variety of other
ways as
well depending upon considerations including, but not limited to, the various
types of
distributed systems and devices employed, the data desired to be collected,
and the
structure of the communications network or otlier system. Thus, the
functionality
allocation illustrated in Figure 2 is exemplary only and should not be
construed to limit
the scope of the invention in any way.
III. Exemplary Queries
Directing attention now to Figure 3, details are provided concerning methods
and systems
for defining and posing queries in connection with the data collection and
management
system 200. Such queries may be defined with reference to any of a variety of
different
perspectives concerning the operation or functionality of the wireless network
100 and
associated target wireless devices 400 or other network nodes. The queries may
be
structured in such a way that performance information is gathered about the
effect of a
simple activity, such as a button press by the user, or information may be
gathered about
more complex transactions that involve multiple network layers, such as the
physical
layer, network layer, transport layer and application layer. In particular,
the target
wireless devices have software stacks that communicate with various network
layers of
the cominunications network.
Once collected, the information associated with the software stacks of the
devices can then be correlated, suc'h that information regarding the software
stacks or the
network layers that they communicate with may be packaged together with and
viewed
within the context of the commensurate RF status information, affording a
complete view
of the interdependencies among different layers and more accurate analysis of
the
information. These are exemplary query subjects only, however, and such
queries may,
more generally, be directed to virtually any aspect of the wireless network
100, associated
target wireless devices 400, and any other network node that may be of
interest to a
network administrator or other personnel.
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An exemplary query structure is denoted generally at 500 in Figure 3. The
query
structure 500 may be configured in any fashion consistent with functionality
disclosed
herein. As shown in Figure 3, one way the query structure 500 can be defined
is through
interaction between a network administrator and SQP 201 by way of the
interface sub-
system 212. If defined by a network administrator, the query structure 500
appears as a
to pop-up window or other type of device that allows the network administrator
to make
various selections concexning the nature and scope of the desired query or
queries. While
a network administrator has the ability to intervene with the system and write
a query on
demand, the preferred embodiment of the invention provides for numerous
queries to be
"pre-defined" in reporting sub-system 208 and accompanying profiles stored in
profile
database 206C. As business and technical needs for data collection arise,
these pre-
defined queries are called upon to generate a complete analysis package,
including one or
more data collection profiles and associated reports.
Any number and type of query structures 500 can be constructed to enable a
network administrator to pre-define or create and submit queries regarding
virtually any
aspect of the performance and operation of the wireless network 100, one or
more
associated target wireless devices 400, or any of the services or entities
provided in
association with wireless network 100. Thus, the query structure 500 indicated
in Figure
3 is exemplary only and is not intended to limit the scope of the invention in
any way.
In yet other implementations, one or more query structures 500 are defined
that do
not include any predetermined menu choices. Rather, a network administrator
defines a
highly customized query structure by simply dragging and dropping desired
items into a
basic query structure template. The profile system 206 can be configured to
prevent
definition of queries, and associated data collection profiles, that are
internally
contradictory or inconsistent. In this way, the network administrator receives
some
measure of assurance that no "noise" data will be collected in connection with
a given
query or data collection profile.
Further, queries, as well as the data collection profiles disclosed elsewhere
herein,
may be generated either manually or automatically in response to the
occurrence of one or
more system events or as the result of analysis of previously collected data.
Data
collection profiles contain "triggers" which direct the initiation and
termination of the
data collection activity. Aspects of the definition and use of triggers are
disclosed in
greater detail below.
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Figure 3 conceptually illustrates various aspects of queries. In particular,
query
structure 500 indicates that the network administrator can define a query that
relates to
target devices (502), software applications (504), services associated with
the target
device (506), information concerning the radio frequency system (508) employed
by the
target device, and any of a variety of other considerations or parameters
(510) that may be
of interest to a network administrator or other personnel, including various
aspects of the
data collection and management system itself. Significantly, these queries, in
any
combination, may be directed to one or more of the aforementioned aspects of
activity
occurring on the device or within the network to allow capture of the data
being generated
in association with the activity.
When developing a query related to aspects (502) of a target device, the
developer
can more specifically target the query to characteristics 502A such as
hardware, software,
and other aspects of a device such as target wireless device 400. Similarly, a
query that
relates to applications (504) operating on the target device, can be
specifically targeted to
characteristics 504A such as the performance of applications present on a
target device,
the amount of usage of each such application, and various other aspects of
applications
resident on the target device or otherwise associated with the wireless
network 100.
With continuing reference to Figure 3, a query that relates to services (506)
available to a target device can be defined for =specific services 506A,
including IP,
messaging, voice transmissions and various other services associated with
wireless
network 100. In similar fashion, a query can be directed to RF related aspects
(508) of
wireless network 100 and/or target wireless devices 400, such as RF
performance
parameters, problems, and other considerations.
Embodiments of the data collection and management system 200 enable one or
more network administrators or other personnel to define and implement a
query, or
queries, directed to virtually any aspect of the wireless network 100 and/or
associated
target wireless devices 400 in which the administrator(s) may be interested.
As a result of
such functionality, a network administrator is not limited to a prescribed
choice of query
subjects but may more generally define one or more queries directed to aiiy
subject matter
that may be of interest. Moreover, query structures 500 and their related
systems enable
specific types of queries that correspond to a particular set of interests to
be generated and
used.
For example, some query structures 500 are concerned only with information
that
would be of interest to the marketing departrnent such as the prevalence of
applications
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used. As another example, an accounting department, either alone or in
connection with a
marketing department, may desire to utilize a query correlating the various
service plans
with particular groups of end users and the behavior of those end users. As
another
example, technical personnel associated with the wireless network 100 and
associated
target wireless devices 400 may desire to invoke queries concerning various
performance
aspects of the network and the target devices. Technical personnel may further
be
interested in the performance of other network nodes such as a media server or
a packet
data serving node. Accordingly, such personnel would have access to numerous
pre-
defined queries as well as the query structures that would enable them to
quickly and
easily define multiple useful queries that could be used to identify problems
and improve
service.
The foregoing query sets may all flow from a single query structure 500 or, as
discussed above, may each constitute a distinct query structure accessible
only to
particular personnel. These are exemplary implementations only however, and
the scope
of the invention should not be construed to be limited to these examples.
IV. Exemplary Data Collection Profiles
As noted above, a wide variety of pre-defined queries concerning numerous
aspects of wireless network 100, the associated target wireless devices 400
and other
components that make up wireless network 100 can be used by the data
collection and
management system to monitor and collect performance data. As noted above, on
occasion a network administrator may also create a custom query on demand.
Once the
query or queries have thus been defined, and it is determined that existing
data is not
sufficient to satisfy the query, a CTR will cause one or more data collection
profiles to be
generated or selected to direct the target wireless devices 400 or other
network nodes in
the collection of data responsive to the query or queries.
In the exemplary embodiment, the data collection effort is pushed out to the
population of target wireless devices 400 for the data collection activity.
The data
collection overhead imposed on each of the target wireless devices 400 is
minimal since
the demand on each device, including any pre-existing tasking requests has
already been
considered as part of the device selection criteria. Moreover, as disclosed
herein, the
collective capabilities and efforts of the various target wireless devices 400
provide a
powerful mechanism for readily and effectively collecting data responsive to
queries.
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With the foregoing in view, attention is directed now to Figure 4 where
aspects of
a data collection profile 600 are illustrated. As generally indicated in
Figure 4, the data
collection profile 600 includes a variety of parameters 602 that define not
only a set of
data that is to be collected, but also the conditions under which data
collection will take
place and the manner in which that data is to be collected and processed. In
this regard,
lo the data collection profile 600 constitutes a refinement of the associated
query in that the
data collection profile 600 is directed to specific types and quantities of
data that, when
gathered and processed, are responsive to the query defined by way of the
query structure
500.
The data collection profile 600 can be configured to become active (i.e.
commence collection processes) and/or become inactive at a certain time or
after a
particular period. The data collection profile 600 and/or its constituent
collection
directives may also expire after a certain period of time. Upon expiration of
the data
collection profile or its constituent data collection directives, the device
may revert to its
default profile or it may notify SQP 201 via MCS 202 of the expiration,
whereupon it is
instructed to receive another profile. In either case, the expiration
capability enables the
device to effectively "purge" obsolete profiles or individual collection
directives and be
ready to receive new profiles or collection directives. The data collection
profile may
also be configured to include multiple triggers which initiate and terminate
data sampling
over some period of time and in response to certain occurrences. In one case,
data
collection may occur in response to a trigger that is defined as the
occurrence of an event.
In other cases, data collection may be initiated or terminated in response to
a trigger that
is defined as the lack of an event occurrence. For example, a data collection
profile may
specify that data collection begins upon arrival in a certain geographical
area and abort if
the user fails to receive a voice call within one hour of entering the
specified geographical
area. In this case, entry into the specified geographical area is the
initiating trigger that
causes data collection to commence, data is buffered, and when the voice call
fails to
occur within one hour, the abort trigger causes data collection to cease. In
this case, the
buffered data is not transformed into a metrics package, and it may or may not
be deleted.
In some cases, data collection may end and then recommence should a specified
network event occur. Should this second event fail to occur, that is, the
trigger is not
activated within a subsequent period of time, the data collection profile may
expire. The
data collection profile may also contain instructions for the conditions under
which
collected data is transformed into a metrics package, and whether and when the
metrics
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package is uploaded to the metrics collector 202A. In other cases, the data
collection
profile 600 may instruct that information about both the occurrence and non-
occurrence,
as applicable, of specified events, as well as whether data has been collected
or not during
some period of time be reported to the metrics collector 202A.
In the exemplary embodiment, the profile builder 206A of the profile system
206
operates in comzection with a target device database 204C to facilitate
definition of a data
collection profile 600, and to define the set of target devices to which the
data collection
profile 600 will be transmitted. As indicated in Figure 2, the profile sub-
system 206
includes a profile editor 206B that enables a network administrator to
retrieve and edit
one or more existing data collection profiles in the event that circumstances
require a
manual change to those data collection profiles. Moreover, once completed, the
data
collection profile 600 may be stored in a profile database 206C for reuse,
backup
purposes and/or for further editing, copying, or other processes.
In any case, the data collection profile 600 illustrated in Figure 4
specifies, among
other things, the type or types of data that are to be collected in connection
with the data
collection profile 600. As suggested earlier, the data collected in connection
with the data
collection profile 600 may comprise virtually any type of data concerning
wireless
network 100 and/or target wireless devices 400. Thus, the data desired to be
collected
may relate to the iJI of the target wireless device 400, the application or
applications
resident on the target wireless device 400, the network services accessed by
target
wireless device 400, the performance of other network elements such as
application and
network servers, and considerations concerning the various network layers,
such as the
transport layer and physical layer.
In addition to specifying various data types, the illustrated data collection
profile
600 can also specify a time parameter, namely, the time frame, or time frames,
during
which some or all of the specified data is to be collected. For example, as a
result of
reports of dropped calls in a particular area, a data collection profile is
generated that is
directed to dropped call analysis. In this case, the data collection profile
may specify that
data collection is to begin as soon as the wireless device enters a certain
geographical
area. The collected data enters a buffer on the device so that it can be
included as part of a
metrics package if a trigger occurs that causes a metrics package to be
created. The data
collection profile may further specify as part of the data collection rules,
that a five
second buffer of information preceding every call occurring while the device
is in the
specified geographical area is to be saved, and that data be collected for the
duration of
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the call. In the event that the call is dropped, an additional five seconds is
captured after
the call drops and the data captured before, during and after the call is
contained in a
metrics package.
In some cases, the data collection profile may specify that certain data be
collected
on some type of predefined schedule. In other cases, the data collection
profile 600 may
lo specify that some data be collected on a regular or periodic basis, while
other data is
collected only once, or on some other non-periodic, irregular basis. In still
other cases,
the data collection profile may have predefined start and/or stop dates that
specify that,
notwithstanding any other conditions, data collection must commence on one
particular
date and/or terminate on another particular date.
With continuing attention to Figure 4, the data collection profile 600
includes,
refers to, or implicates various triggers which are used to determine if and
when a data
collection process specified in the data collection profile should initiate,
abort, and
terminate. For example, one teclmique known in the art for initiating a
network-based
instant connect communication (also known as Push to Talk 8) is for an
originating
wireless device to send a Session Initiation Protocol (SIP) INVITE to a
network-based
instant connect server to request the participation of one or more terminating
wireless
devices in the communication session. The INVITE is received by the instant
connect
server and sent on to the terminating wireless device. If the terminating
wireless device
has been active recently, the server may send a "100 trying" message to the
originating
device while it goes on to attempt contacting the terminating device.
Typically, when the 100 TRI'ING message is received at the originating device
along with an indication that the floor is open, the originating device begins
to send voice
data. While the originating device is busy sending voice data, the instant
connect server
may have tried and failed to actually reach the terminating device, and a 408
TIMEOUT
message is sent to the originating device. At this point, the user of the
originating device
has had a very poor user experience. At the same time, the service provider
has no ability
to capture all of the transactions that happened or failed to happen between
the originating
wireless device, the instant connect server, otller participating network
elements such as
the Packet Data Serving Node (PDSN), and the terminating handset. Thus, it has
no data
with which it can troubleshoot and solve the problem.
Using the methods disclosed herein, one embodiment provides for a data
collection profile resident on the originating device to begin collecting data
when an
initiating trigger is activated - in this example, origination of the instant
connect
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communication attempt. Receipt of the aforementioned 408 error message by the
originating device is a terminating trigger condition that causes the SQC 402
resident on
the originating wireless device to stop data collection and prepare a metrics
package for
upload to metrics collector 202A. In some cases, a trigger may cause the data
collection
activity to abort without creating a metrics package. In the exemplary
embodiment, the
data collection profile has been further configured to specify that receipt of
a 408. error
constitutes a condition under which a metrics package is to be immediately
prepared and
uploaded to metrics collector 202A, and the metrics package is uploaded
accordingly. In
this example, the terminating wireless device is unaware that a communication
attempt
has been made, so no trigger has been activated on the terminating device to
initiate data
collection and/or to cause creation of a metrics package. To ensure that
important data
related to the communication attempt is collected from the terminating device,
receipt by
metrics collector 202A of the metrics package from the originating wireless
device may
result in a command, such as an SMS message, being sent to the terminating
device. This
command activates a trigger which causes an "on-demand" data collection
activity on the
terminating wireless device, forces any additional data collection needed, and
uploads the
metrics package at a specified point in time. It should be noted that the "on-
demand"
collection activity may occur in addition to unrelated data collection
activity that may
already be occurring on the device as part of its normal operation. In another
case, the
terminating device could have a profile that directs it to continually collect
data
specifically associated with an issue that is being investigated; in this case
it would be the
timing and frequency of INVITE reception. As a result of the on-demand upload,
the
history associated with this specific area of concern is uploaded to provide
complete
visibility of the events occurring on the terminating device and the data
surrounding the
408 issue being investigated. Additionally, in some situations, collected data
can be
subjected to processing at the device, such as minimum/maximum/average/count
type
processing or other calculations that aggregate or otherwise reduce the amount
of data
that is to be transmitted from the device to the SQP. In this case, the data
that is sent to
the metrics collector has already undergone some processing and is not merely
raw
collected data.
In another embodiment, an SQC may reside on another network element, such as
the instant connect application server, and a data collection profile may be
configured to
immediately prepare and upload a metrics package upon the occurrence of a 408
error. In
this case, upon recognition of a 408 error by the instant connect application
server, the
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SQC causes a metrics package to be created and uploaded to metrics collector
202A.
SQP 201 then causes the SMS message to be sent to the terminating device,
whereupon
an "on-demand" data collection activity on the terminating device begins and
proceeds as
noted previously. More particular information concerning triggers as they
relate to the
data collection profile and various other aspects of the data collection and
management
system 200 is provided elsewhere herein.
At the same time as the metrics packages are being prepared on target wireless
devices 400, SQP 201 may queue an analysis task in reporting sub-system 208
which is
prepared to analyze the metrics packages received from the originating and
terminating
wireless devices, and from any other network elements equipped with data
collection
profiles that are associated with the instant connect communication attempt.
The metrics
package generated at the terminating wireless device is assigned an identifier
that
associates it with the metrics packages generated at the originating wireless
device and/or
those generated at the instant connect application server and any other
network elements
associated with the transaction. At any time, queries may be run against
reporting sub-
system 208 to identify metrics packages that are associated with other metrics
packages
so the complete sequence of events that occurred aniong all of the network
elements
involved in transactions among the devices can be viewed, tracked and
analyzed. Reports
generated from reporting sub-system 208 may be stored for later use in
reporting database
208C or the underlying data may be exported to a third party reporting system
via the
interface sub-system 212. Additionally, in some embodiments, notifications
concerning
receipt of the data or results of the analysis can be sent to other systems as
well as to
network administrators and other personnel.
As another example of a parameter that is used to guide data collection
efforts, the
data collection profile 600 can specify certain geographical constraints and
limitations.
More particularly, such geographical constraints may specify that data is to
be collected
only by target devices that place or receive calls within specified
geographical boundaries
or by those within a certain proximity to a particular base station. The data
collection
profile may further specify that only those devices experiencing a particullar
problem in a
certain geographic area should,collect data. Such information may, for
example, enable
network administrators and other personnel to isolate a recurring problem in a
particular
area, pinpoint its origin, and make clear the steps for rectifying the
problem. For example,
such geographical information may also be used to help identify malfunctioning
base
stations or other equipment in the event that there is an inordinate number of
dropped
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calls within the defined geographical limits. The information may further help
identify
where equipment, such as signal enhancement equipment, should be placed in the
network to improve service. Additionally, geographical information enables
development
of graphical depictions, such as maps, that indicate the locations and
concentrations of
various conditions and/or problems with wireless network 100.
As further illustrated in Figure 4, the data collection profile 600 specifies
particular services concerning which data is to be collected. Some
implementations of the
data collection profile 600 may specify that transmission signal ("Tx")
strength data be
collected for Internet Protocol (IP) data calls initiated by an instant
connect
communication session. In other cases, the data collection profile 600 may
specify that
data is to be collected concerning messaging services accessed by the target
wireless
device 400. Because the wireless device participates in each service delivered
to the end
user and utilizes a software stack that communicates with each network layer
necessary to
deliver the service, the ability to collect metrics in relation to a specific
service, and
ignore those metrics when not utilizing the service, provides a significant
benefit over
existing solutions. For exainple, to monitor the transmit signal strength
under the
conditions described above, a network probe known in the art would have to
monitor all
transmit power, for all wireless terminals, across all transports (voice or IP
for example),
for all services (telephony,= messaging, browsing and instant connect
communication for
example). The scale and scope of this data collection process effectively
makes this data
uncollectible by any methods other than those disclosed herein in conjunction
with the
present invention.
In some cases, a data collection profile can be defined that collects
information
about the performance of services, but only when other aspects of the system
are in
certain configurations. For example, a query could involve analyzing the poor
performance of Wireless Application Protocol (WAP) browser pages on the
service
provider's portal from certain locations. A WAP browsing session utilizes the
IP layer,
which runs over the RF layer to connect to a large IP network, then to a WAP
Gateway,
and through another IP network to the portal in question. Any one of these
systems can
cause performance degradation, but RF degradation is a frequently encountered
problem.
Therefore, it would be useful to be able to filter out the .RF related data so
that other
possible sources for the poor performance may be uncovered. In this case,
target wireless
devices 400 are equipped with a data collection profile tuned to collecting
data about very
specific network conditions under which a WAP page load takes longer than a
certain
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configured time. A request by the device for a WAP page load is the initiating
trigger
that causes data collection to begin. The data collection profile analyzes RF
performance
criteria such as frame loss, and automatically ignores events that occur in
high loss
situations. Since RF is typically the least reliable element in the network,
this simple
filter dramatically increases the value of the reported information by
ensuring that the
most frequent, and in this case irrelevant, cause of the delay in loading the
WAP page is
ignored, allowing the focus of the data to be on the higher layers. Similarly,
the data
collection profile could also ignore results that are gathered in scenarios
where the IP
service is not performing properly. Furthermore, since the wireless device
contains
software implementations of all the service layers, the data collection
profile can be
defined to compare information from any layer in order to qualify analysis
operations.
In other cases, the data collection profile can be defined in a way that
utilizes the
parameters and status of other services on the wireless device to filter data
collection.
The wireless device has many different services running on it, such as voice
calls,
messaging, games, and cameras. These services interact both on the device
(contention
for resources such as processor and battery) and in the network (contention
for
bandwidth). The number of these services is rapidly -increasing, and systems
such as
BREW and JAVA allow users to download their own selection of services, after
the
wireless device is in the user's possession. Thus, the growing number of
potential
interactions between these services, and the difficulty in analyzing all
possible scenarios
virtually guarantee that numerous failures will occur due to these service
interactions.
For example, multimedia messaging service (MMS) systems use a model where
messages are downloaded "in the background" to the user's wireless device to
provide an
"instant access" experience. An application like instant connect
communication, also
known as Push to Talk , has very demanding requirements and expectations for
the data
chamzel. If an MMS download occurs during an instant connect communication
session,
the user's experience may be highly impacted, and the instant connect
communication
session may not perform as it should. The cause of this problem is invisible
to the user, so
no amount of interaction with customer care will resolve why instant connect
communication sessions occasionally deliver very poor performance. To address
this, a
data collection profile can be defined with an initiating trigger that causes
data collection
to begin any time multiple applications or services are requesting data access
simultaneously. Data collected in accordance with this profile enables the
service
provider to evaluate this and any other unanticipated contentions between
services.
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The data collection profile 600 also specifies various parameters concerning
the
handling and management of the data collected by the target wireless device
400. In the
illustrated embodiment, the data collection profile 600 specifies a schedule
according to
which data gathered by the target device is to be uploaded to the SQP 201. In
one
implementation, the data collection profile 600 specifies a regular upload
schedule, while
other data collection profiles 600 may specify a one time upload, or real time
upload of
collected data. As with other aspects of the data collection profile 600, the
upload
schedule may be configured as necessary to suit the requirements of a
particular
application, operating system, or target device. The upload schedule may also
be event
driven, and it can be dependent on other factors including end user activity,
available
device battery life, and coverage status. For example, an upload may be
skipped or
delayed if the battery of target wireless device 400 is low, so as not to
impact the user's
experience significantly by decreasing the limited power available. Another
example of
how to preserve user experience is that the SQC 402 can build an activity
pattern for the
end user and adjust the upload schedule called out in the collection profile
to an
empirically derived low-usage time.
As noted above, the upload schedule can be based on the status of the target
device. This status can relate to events or conditions of the target device
itself. In
addition, the status of the target device can also relate to the conditions of
the network
and the interaction of the target device within the network. For example,
conditions of
the network that can determine the upload schedule include the signal quality,
high or low
contention, non-roaming service, the existence of high speed data service,
etc.
In another example, the RF environment is analyzed, and a target wireless
device
400 can determine whether it is efficient for both the device and the network
to upload a
metrics package. For example, the amount of power a wireless device consumes
for a
data transmission depends upon the power level required to achieve adequate
signal to
noise ratio with a tower. A metrics package upload that is not time critical
could be
configured to only proceed if the power setting was below a preset maximum.
This
ensures that only minimal power was consumed for the operation. Further
refinement of
this model could include varying the preset maximum power based on the amount
of time
the upload has been delayed.
Further aspects of the data collection profile 600 include the ability to
specify the
device configuration with which the collection profile is compatible. As more
and more
user definable and downloadable features become available for wireless
devices, it will
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become impossible for target device database 204C to have all information
about every
aspect of target wireless device 400. For example, users can download
customized
ringtones which make use of multiple different models for playback. If a
suspected issue
only appears to occur with devices that attempt to play back MIDI based
ringtones that
are over 30 seconds in length, a data collection profile could be defined and
a target
population of wireless devices selected, but the data collection profile would
only activate
if the target wireless device 400 had that particular configuration. In this
case, while the
data collection profile could be downloaded to a large population of devices
that meet
certain known criteria, it would only activate on the specific devices that
use MIDI based
ringtones over 30 seconds in length. The target wireless devices 400 that are
not
compatible with the data collection profile 600 can either ignore the data
collection
profile 600 or purge it from the memory of.the target device. Among other
things, this
functionality helps to foreclose the gathering of irrelevant or extraneous
data.
The data collection profile 600, in some cases, incorporates various other
related
functionalities. For example, one or more data collection profiles 600 include
instructions
that specify what action a target wireless device 400 must take if conflicting
data profiles
are in effect for that target wireless device 400. As another example, some
data collection
profiles 600 include instructions that specify the priority of the data
collection activity
specified therein relative to one or more others associated with the target
wireless device
400. While multiple data collection profiles inay be executed simultaneously,
the need
for prioritizing data collection profile execution may arise when there is
higher urgency
associated with the required data, or when the device is a match for the data
collection
requirements of multiple queries, and where the capacity of the target
wireless device 400
is such that simultaneous collection of data streams, specified by two or more
data
collection profiles 600, cannot be achieved. To address this potential
conflict, data
collection profiles may be assigned a priority l'evel, and once downloaded to
the device,
the relative priority levels are assessed by SQC 402 resident on the device
and profiles
may be executed according to their respective priorities. Once data is
collected in
accordance with the priorities specified in the data collection profile, a
metrics package
may be created and placed in the metrics archive of SQC 402. Such
functionalities are
exemplary only however, and various other rules concerning the management of
data
collection profiles 600 may also be used.
As mentioned previously, the data collection profile 600 can specify, include
or
otherwise incorporate other information, guidelines or rules concerning the
data that is to
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be collected, as well as the conditions under whicll such data will be
collected. Some data
collection profiles 600 include disqualification criteria that enable a target
wireless device
400 to self-select itself out of the data collection process. The data
collection profiles 600
may also include or specify various parameters concerning the hardware and/or
software
contained in, or associated with, one or more target wireless devices 400.
1o As noted earlier, data collection profiles may be defined and stored for
later use,
or they may be created "on-demand" in response to certain business and
technical needs.
Additionally, in many cases, data collection profiles are automatically
derived from
particular data that is observed after analysis of metrics packages. They may
also be
generated when certain thresholds are reached or trends are identified. Thus,
data
collection profiles are derived from one or more characteristics of collected
data, such as
trend information, predefined data points or thresholds. As an example, a data
collection
profile may be configured to collect RF performance information such as
dropped calls,
but not radio data. An inordinate number of dropped calls in a particular
geographic area
would, in this example, serve as a basis for modification of the existing data
collection
profile, or generation of a new data collection profile, that is more
specifically directed to
radio data collection so as to enable evaluations and diagnoses concerning the
relatively
large number of dropped calls. Thus, even though radio data was not the
initial focus of
the data collection effort, trend or threshold analysis of the collected
metrics packages
provides a basis for further, related, data collection efforts.
V. Exemplary Query Definition Process
Directiilg attention now to Figure 5, details are provided concerning a
process 700
for defining a query such as may be used in the subsequent development of a
data
collection profile. As previously noted, a large number of business and
technical issues
can be identified and complete data collection packages, including data
collection profiles
and reports, can be developed and stored for later use. However, in some cases
human
intervention may be necessary to react immediately to a sequence of previously
unknown
events, and a network administrator may wish to create "on-demand" data
collection
profiles. The mechanism for creating data collection profiles on-demand is
depicted in
Figure 5. At stage 702 of the process 700, the threshold question that is
intended to be
answered by the data collection effort is identified. As suggested in Figure
5, the
identification of the threshold question stage of the query process may be
based on results
of various other reports that have been generated concerning prior data
collection efforts.
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In this way, the network administrator may be able to sharpen the query using
previously
developed knowledge. This, in turn, enhances development of the associated
data
collection profile. At this point, the threshold question may constitute
nothing more than
a plain language statement or question as to the particular data desired or
question to be
addressed.
Once the threshold questions have been identified, the process 700 advances to
stage 704 where the network administrator accesses a query screen by way of a
UI. The
process 700 then advances to stage 706 where the network administrator employs
the
query screen to refine the threshold question, or questions, identified at
stage 702. As
discussed above in connection with Figure 3, such refinement of the threshold
question
can be implemented by way of a query structure which uses trees, cascading
menus
and/or other structures and devices that enable a network administrator to
refine the issue
or issues to be addressed by the data collection effort.
A network administrator may specify a query that relates to a particular
target
device or type of target device, applications that are installed on the target
device,
services that are accessed in connection with a target device, as well as the
RF
performance or the performance of other systems in connection with which the
target
device is employed. As indicated at stage 708 of the process 700, this
development of the
query structure may if desired, consider and otherwise incorporate aspects of
previously
developed queries and/or the data and results obtained in connection with such
queries.
Next, the process 700 advances to stage 710. At this stage, the network
administrator finalizes the query based on the various information categories
specified as
well as, if applicable, the structure and/or results of one or more previously
developed
queries. At such tinle as the query has been finalized, the query is then
transmitted to the
reporting sub-system 208. The finalized queries can be stored in memory so
that they can
be readily retrievect and modified if desired. Further, the stored queries may
also be
retrieved and copied so as to streamline the development of future similar
queries. In
addition, such queries can be stored in a searchable database so that the
network
administrator can quickly determine if the query in which he or she is
interested has
already been developed. This arrangement likewise enables streamlined
development of
additional queries and data collection profiles. If the data necessary to
satisfy the query
has already been collected, the appropriate data and/or reports are returned
to the network
administrator. If not a CTR is geiierated by reporting sub-system 208 and
communicated
to tasking sub-system 204.
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VI. Exemplary Tasking, Data Collection Profile Building and Target Device
Selection Processes
With attention now to Figure 6, details are provided concerning a process 800
for
generating, or building, one or more data collection profiles based on a CTR,
selecting the
target devices to receive the profile, and downloading the profile to the
target devices. At
stage 802 of the process 800, the CTR is received at the tasking sub-system
204. In some
cases, a stage 804 is entered where development of the data collection profile
is initiated
in response to the receipt of trigger information concerning the occurrence of
a trigger
condition, or set of trigger conditions. Thus, some or all of a data
collection profile may
be generated automatically.
In yet other implementations, the data collection profile is generated when
requested by a network administrator through the submission of a finalized
query
structure and a resulting CTR. In order to facilitate relatively rapid
development of data
collection profiles, the profile system can be configured to search for data
collection
profiles, such as in the profile database that match or are substantially
responsive to the
CTR. In this way, development of the new data collection profile can proceed
fairly
quickly. Moreover, in some cases, the network administrator may specifically
direct that
a particular data collection profile be modified in a particular way so that
the modified
data collection profile can be populated to various target devices. In this
case, the
discretion to use previously developed data collection profiles is taken from
the profile
system and given to the network administrator instead.
In either case, the process 800 then advances to stage 806 where the CTR is
provided to the profile builder 206A. At stage 808, the profile builder 206A
generates
data collection directives, including rales and triggers, corresponding to the
CTR and/or
retrieves existing data collection directives, as applicable. With the data
collection
directives having been thus generated and/or retrieved, the process 800
advances to stage
810 where the profile builder 206A builds the data collection profile, or
modifies an
existing data collection profile, as applicable.
After the data collection profile has been selected, built or modified, as
applicable,
a determination must next be made as to which target device, or target
devices, will be
used to collect the data identified in the data collection profile.
Accordingly, at stage 812
of process 800, the profile sub-system 206 notifies the tasking sub-system 204
of the
device requirements in the data collection profile. Based on this information,
the tasking
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sub-system 204 accesses the tasking database 204B and target device database
204C and,
at stage 814, identifies the target device or devices whose characteristics
are consistent
with or otherwise correspond to the data collection profile. As mentioned
previously, any
number of device characteristics and conditions may be considered in the
device
qualification and selection process. In one embodiment in which wireless
devices are
1o used for data collection, the qualification process includes methods to
determine which
wireless devices are compatible with the data collection profile and which
wireless
devices must be disqualified from the data collection activity. To fiirther
qualify or
disqualify wireless devices, consideration may be given to various other
factors and
characteristics such as the configuration of the device, physical properties
such as
available memory, location, and available battery life, usage properties such
as account
status, usage patterns, reported service problems and other usage history,
interaction with
or physical manipulation of the device by an end user, applications installed,
and the
profile of the end user.
The device information and characteristics used in the device targeting and
selection process at stage 814 can come from many sources, including systems
controlled
by the network operator, such as an HLR or VLR, or from information provided
to target
device database 204C when the device initially activates SQC 402.
Additionally, device
information can be extracted from previous data collection activity and stored
in target
device database 204C, or it can be specifically collected for the purpose of
populating
device "targeting data" to the target device database through the use of a
data collection
profile whose data collection directives are focused on this data collection
goal. An
example of this is a data collection profile that is downloaded to every known
device and
directed to recording the identity of the base stations encountered by each
device during a
seven day period. At the end of the seven day period, the collected data is
uploaded to
metrics collector 202A and communicated to target device database 204C; the
targeting
data is then stored for later device targeting purposes. Thus, the device
targeting and
selection process would then have access to data concerning the identity of
base stations
encountered by the devices and the frequency with which those devices
encountered a
particular base station. Accordingly, a particular issue investigation may
involve certain
base stations, and the devices that can provide the best performance data
concerning those
base stations can then be targeted to collect data for that investigation. As
a result of the
process of collecting targeting data into target device database 204C and then
using that
data later for device selection criteria, a set of target devices can be
identified and selected
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based on any metrics that are visible to SQC 402. These could include ainongst
others
radio information and network information, real time device configuration
included user
downloaded software and content, user behavior history including access
patterns and
application usage patterns, device characteristics and configuration such as
battery type or
attached accessory devices.
The targeting process depicted at stage 814 of Figure 6 can also automatically
select devices that have previously encountered particular issues or problems.
For
example, if a population of devices has experienced a failure that is known to
the data
collection and management system 200, the reporting subsystem 208 may
automatically
cause a data collection profile to be generated in order to further explore
the failure, and
the devices that experienced the reported failure may be selected to receive
the new data
collection profile and participate in the data collection activity.
The device selection process may be iterative in that the initial results from
the
target device search may yield too many or too few compatible devices for
example. In
this case, the selection criteria can be modified incrementally to yield an
appropriate
target device population. In the example of encountered base stations
discussed above,
initial selection criteria might limit the devices selected to those that have
encountered a
specific base station in the last week. However, if this results in more
devices than needed
for data collection, another iteration of the selectioii process may specify
selecting
devices that have encountered the base station in the last two days, which
could yield a
more desirable number of devices for the data collection activity. In
practice, this
iteration will typically be done automatically by the tasking sub-system in
the process of
selecting devices.
Another source of data for the device targeting and selection process of stage
814
can be the device user's account information typically stored as part of the
network
operator's billing and provisioning system. This information identifies
external properties
of the end user and the end user's financial relationship with the network
operator. This
information can include corporate affiliation, billing plan and style,
customer care history
and events, and user demographic information. An example use of this
infonnation
would be a query that monitored the performance of devices associated with a
certain
high value corporate customer. By tracking certain performance parameters such
as
dropped calls versus successful calls for devices with a specific corporate
affiliation, the
network operator could offer a guarantee of a certain level of performance,
against a
refund of a percentage of the monthly fee. In a market where perceived quality
is a key
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driver for selection of a network operator' services, such a program could
offer significant
competitive advantages.
Furthermore, if the data collection profile specifies that data is to be
collected
concerning wireless calls made in the San Francisco Bay area, the tasking sub-
system 204
will likely not select target devices whose account information indicates that
the device
resides in New York, unless the target device database 204C indicates that the
device is or
was recently active in the San Francisco Bay area. Note that in other cases,
the tasking
sub-system 204 accesses the profile developed by the profile system and the
tasking sub-
system 204 makes a determination as to the target devices to which the data
collection
profile will be transmitted. The results of this determination are then
transmitted to the
profile builder 206A so the device compatibility information can be included
in the data
collection profile.
After the target devices have been identified, the process 800 advances to
stage
816 where the new or updated profile, as applicable, is transmitted to the
identified target
device(s). Profile transmission can occur in a variety of ways, including
"pushing" the
data collection profile to the target device, sending a message, such as an
SMS, to the
target device prompting it to retrieve the data collection profile, and
preparing the data
collection profile for download the next time the target device contacts SQP
201 such as
when it uploads a metrics package. Such profile transmission to'the SQC 402
residing on
the target device(s) may be achieved using any of a variety of transport
mechanisms and
standards including Short Message Service ("SMS"), Hypertext Transport
Protocol
("HTTP"), Hypertext Transport Protocol Secure ("HTTPS"), Wireless Application
Protocol ("WAP") Push, IP-based Over-the-Air (IOTA) protocol, OMA/DM, or other
protocols that are known in the art or that may be developed in the future.
The process 800 then advances to stage 818 where the data collection profile
is
stored on the target devices. When received by a target device, the collection
profile is
processed by SQC 402. In some cases, the data collection profile may be stored
as
received, or integrated with or take the place of previously received data
collection
profile(s). Factors that affect the how the data collection profile is
processed by SQC 402
include, but are not limited to, the suitability of the device to the data
collection
requirements defined in the data collection profile, the relative priority of
the data
collection profile and any previously received profiles, and any explicit
processing rules
stated in the data collection profile. If processing the new profile by SQC
402 results in
the data collection activity differing in any way from that specified in the
data collection
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profile (e.g. if the device self-selects out of the data collection activity),
SQC 402 may
communicate back to SQP 201 the specifics of how and why the data collection
activity
differed.
The data collection profile can be transmitted to the target devices over a
wireless
or wireline connection. Because the data collection profile is relatively
small, the
1o transmission of the data collection profile proceeds relatively quickly and
imposes
minimal processing overhead on the target devices. Further, the population of
target
devices can be quickly redefined and data collection profiles quickly and
easily
downloaded in order to achieve data collection goals. Such iterative data
collection
processes are particularly useful in understanding transient error conditions
because of the
speed with which the data collection activity can be refined. Other data
collection
activities may contribute to more long term trend analyses. For example,
thresholds might
be set with regard to performance degradation that, when reached, would cause
generation and download of a data collection profile to a population of
wireless devices.
In this manner, additional data collection can take place that would enable
further
exploration of the problem. Consequently, embodiments of the data collection
and
management system are highly flexible and data collection efforts can be
quickly refined,
reconfigured, and redirected in response to rapidly emerging network
conditions or
transient network conditions. In any case, statistical analyses performed in
connection
with the collected data can rapidly converge on a solution or answer to the
question posed
in connection with the query.
Unlike systems known in the art, the data collection and management system
does
not rely on the end users of the target devices to download the data
collection profiles or
to otherwise take action to enable the data collection process. Rather, as
indicated above,
the update of the target devices proceeds with minimal or no involvement on
the part of
the end user of the target device. Moreover, because each target device has
been carefully
qualified for participation in the data collection activity, the likelihood
that any particular
target device is not a valid candidate for a collection task is minimized.
Thus, the
collection of data as specified in connection with the data collection and
management
system 200 is performed quickly and easily by the target devices. Moreover,
because the
data collection profile is typically generated automatically in response to
the occurrence
of certain network conditions, the flexibility and speed with which the data
collection
management system 200 operates is further enhanced.
VII. Data Collection and Processing
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The data collection function of data collection and management system 200 is
based around one or more metrics which are generated by the software or
hardware of
wireless device 400 during its operation, and which are indicative of device
and network
performance. In one case, during the device manufacturing process, software
commands
are integrated into the operating system or other device software that cause
metrics to be
generated. As the metrics are generated, they are transformed into a data
structure that is
used to invoke SQC 402. As SQC 402 is presented with the generated metrics, it
determines, based on the data collection profile(s) under its governance,
whether a given
metric is of interest at the time it is generated, and if so, it may store the
metric into a
buffer, where it is available to be included in a metrics package at some
later time. The
process of storing metrics into buffers is referred to as collecting metrics.
However, it
should be noted that in some cases, the generated metrics may be collected
directly into a
metrics package without having first been buffered. Otherwise, the process of
metrics
generation and buffering can occur constantly as part of the basic operation
of wireless
device 400. The control of this data collection logic is further described
below in Figure
7.
Another mechanism for generating metrics on wireless device 400 involves
integrating the software for creating the metrics with application software
that is
embedded on or downloaded onto the wireless device; this is in contrast to
integrating
metric-generating commands with, for example, the operating system software of
the
wireless device during the device manufacturing process. During the
development of the
application software, an application programming interface (API) is used that
allows the
application developer to invoke SQC 402 with metrics generated by the
application.
In one embodiment of the invention, when SQC 402 is presented with generated
metrics, the SQC only interprets metrics in certain fields of the metrics data
structure, and
the remaining metrics are processed without any additional handling by the
invention, but
by techniques known in the art such as mark-up languages or variable length
structures.
The APIs reflect an in-memory data structure model that is generated from an
XML
description shared between the SQP operator and the application developer via
external
means. The common fields of the metrics data structure include a unique
identifier
(assigned by the SQP operator during the XML exchange process) and size
fields, and
allow new metrics to be generated by new applications and without modification
to SQC.
Rules in the data collection profile direct assignment of metrics to buffers
and link
triggers to generated metrics by matching the identifiers in the common
aspects of the
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metrics data structure. Data collection profiles can be implemented that
define data
collection rules, triggers and buffers for metrics requirements that arise
after production
and implementation of the SQC.
The extendable metrics model can be implemented both for third party
applications integrated with the wireless cominunication device (such as
browsers and or
messaging applications) and for applications that are downloaded into virtual
environments such as BREW or Java Virtual Machines. The virtual environment
implements the programming interface for invocation by the application
developed to the
SQC enabled platform and functions as described above. Each time the interface
is
invoked the metric data structure is passed to SQC as a metric.
Virtual machines as described above provide another important point for
generation of inetrics. By specifically instrumenting the virtual machine to
generate
metrics, all applications that run on the virtual machine, whether utilizing
programming
interfaces as described above or not, are therefore instrumented for some
degree of
metrics generation. In the exemplary embodiment, the following aspects are
instrumented to generate metrics, but substantially any aspect of the wireless
device 400
functionality can generate metrics. Metric generation includes all error
display routines
allowing errors displayed to users to be captured by the data collection and
management
system for later analysis. Exceptions (software that violates fundamental
principles of the
target device operation) and task timers (timers that assure no single
function can take all
the processing resources and that detect infinite loop type errors) can
generate metrics
that indicate the state of the application when the error occurred. When
captured and
uploaded, the metrics can enable application developers to find errors in
their software
that occur in the filed and significantly speed problem diagnosis. User
interface routines
including screen refreshes and user input (button presses or other direct
input) can
generate metrics with the user input which include timestamps. When uploaded
the user
interface metrics can be used to understand how users interact with the
application or
device to help optimize application design and detect errors or points of
confusion. These
techniques can also apply to the entire wireless device 400, with the main
operating
system being insttumented instead of the virtual machine.
With attention now to Figure 7, details are provided concerning a process 900
performed by one or more target devices in connection with one or more data
collection
profiles. The process 900 begins with generation of inetrics as part of the
target device
operation. At stage 902 of the process 900, data collection commences as
specified in the
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data collection profile. As noted earlier, such data collection may commence
in response
to an initiating trigger, which could be as simple as the time of day or
arriving at a
geographical location, or it can be a complex combination of conditions, such
as time of
day, geographical location, an encounter with a particular error, or a
combination of any
of the above conditions coupled with use or non-use of a particular service or
application.
lo Once a profile is activated, data collection can begin and proceed
continuously, and it can
start, stop and restart to sample data based on data collection rules and
triggers defined in
the data collection profile. As noted earlier, during the data collection
process, the
metrics can be stored in a metrics buffer, or temporary memory, and may or may
not ever
be used. The metrics buffer is a circular buffer that stores N saniples of
data that is
available for use, in creating a metrics package if necessary. Use of the
buffered data
allows a view of metrics generated before a particular error condition
occurred, for
example. This historical view, along with other metrics surrounding an error
condition,
can be vitally important in analyzing the problem. Thus, in response to a
trigger, the
buffered data can be captured in a metrics package along with any specified
data arriving
after the trigger was activated. In other cases, data can be collected and
written directly to
a metrics package without having first been buffered.
In any case, the target devices commence collection of data as specified in
the
data collection profile. For instance, each of the target devices may first
examine the
received data collection profile to check and verify whether the data
collection profile is
consistent with various characteristics of the target device such as the
hardware and
software contained on the target device and the various services with which
the target
device is authorized for use. In this way, target devices that are incapable
of collecting
the data specified in the data collection profile, or are otherwise unsuited
to facilitate
determination of a response to the query, may self-select out of the data
gathering
process. Alternatively, depending on the compatibility-related instructions
contained in
the data collection profile, rather than self-selecting out of data
collection, the device may
collect only a subset of the requested data and report this back to the
metrics collector
202A along with the basis for the subset collection. Thus, the network
administrator can
be assured that the data ultimately collected and transmitted to metrics
collector 202A
comprises only data that is consistent with, and responsive to, the initially
posed query.
In any case, once the data has been collected, the process 900 advances to
stage
903 where the collected data is transformed by SQC 402 into a metrics package
and
placed in the metrics archive of SQC 402. Because device resources are by
nature
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constrained, SQC 402 may employ methods for managing the priority of metrics
packages stored on the device. For example, each time a metrics package is
added to the
metrics archive of SQC 402, SQC 402 calculates the total non-volatile memory
used. If
the total non-volatile memory required to store a new metrics package exceeds
the
amount of memory allotted to the metrics archive, SQC 402 reassesses the
nature of the
data in each stored metrics package. In one case, and under certain
conditions, one or
more metrics packages may be uploaded to metrics collector 202A to make room
for the
new metrics package on the device. Under certain conditions, SQC 402 may
employ an
algorithm for reviewing the stored metrics packages and selecting metrics
packages for
deletion. The algorithm may consider criteria including data storage
allocations specified
in a data collection profile, the nature and priority of the data, the
timeliness of the data,
the size of the new package to be stored, and the size of the package to be
deleted.
Selected metrics packages are then deleted from the metrics archive on the
device until
there is enough memory to store the new metrics package.
At stage 904 of process 900 the metrics package is transmitted to the metrics
collector 202A at a time specified in the applicable data collection profile
or profiles. As
noted earlier, transmission of the metrics package may be a one time event, or
may be
performed on a periodic basis, or a recurring but irregular basis. It may also
be
transmitted as the result of an "on-demand" command sent to the device by the
system, by
a network administrator or the device user, or as the result of resource
management by the
SQC.
In one embodiment, the data collection profile may specify that the metrics
package upload take place only upon the occurrence of a particular event or
condition.
When the condition for transmission is met, the collected data is transmitted
to the
metrics collector 202A. In some cases, receipt of the metrics package can
generate
notifications, such as email alerts and system alarms, and it can initiate
feporting activity
and/or additional monitoring or data collection activity. In other cases, if
the condition is
met, the current status of the end user's device may be further qualified
before the upload
activity commences to avoid overwhelming the capacity of the device or network
or
otherwise interfering with the end user's normal activity. If the condition is
met, but the
end user is engaged in an activity on the device that would be interrupted by
the
transmission of the metrics package, the transmission can be postponed to a
later time and
uploaded in accordance with a secondary set of rules. The metrics package can
also be
discarded altogether if, for example, the data is time-sensitive and the
device is
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unavailable for connection to the netNvork for an extended period of time or
if SQC
resource management practices force deletion to make room for priority metrics
packages.
Finally, as indicated in Figure 7, the process 900 advances to stage 906 where
it is
determined if a new or modified data collection profile is available for
download by one
or more target wireless devices 400. While this stage in the process is
depicted in Figure
7 as part of a sequential operation, determination of whether or not a new or
modified
profile is available for download is not contingent upon any other stage in
the data
collection process, and such new or modified data collection profiles may be
created and
prepared for download to selected devices at any time in response to changing
network
conditions, sudden emergence of a particular network condition, in response to
generation
of a new query, or various other factors. If a new or modified data collection
profile is
available, at stage 908 the available new or modified data collection profile
is
downloaded to the target wireless devices. Otherwise, at stage 910, in
accordance with
rules specified in the data collection profile, it is determined whether or
not the existing
data collection profile remains active; if so, it resumes data collection
activities at stage
902. In many cases the existing data collection profile may stay on the device
for any
amount of time with or without modification and perform numerous instances of
data
collection and upload. However, if the existing data collection profile is
detennined to be
obsolete at stage 910, the process advances to stage 912 where the existing
data collection
profile becomes inactive, and in some cases it is automatically deleted from
the device.
Directing attention to Figure 8, details are provided concerning aspects of a
process 1000 for the processing and management of metrics packages. At stage
1002 of
the process 1000, metrics package data is accessed from the reporting sub-
system 208.
Metrics packages can be indexed or otherwise related to the data collection
profile and to
other metrics packages so that all of the appropriate data can be accessed
from the
reporting system.
The process 1000 then advances to stage 1004 where the metrics package data is
processed. Such processing can be virtually any type of manipulation or
analysis of the
metrics package data including statistical analysis. In some cases, the
results of the
analysis of the metrics package data are used to develop or refine existing or
future
queries, data collection profiles and/or to improve targeting accuracy of the
tasking sub-
system 204. After collection, and either before or in parallel to the report
generation
operations described below, the data may be augmented using automated
calculations and
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additional information sources. Also, a plug-in server architecture could
allow other
applications to have direct feeds to the metrics packages.
Next, the process 1000 advances to stage 1006 where various reports are
generated based on the processing of the metrics package. In the preferred
embodiment
of the invention, such reports will have been defined in advance in
conjunction with a
lo data collection analysis package as previously described herein and can be
populated with
analyzed data. Alternatively, on occasion custom reports may be created on
demand by a
network administrator. Finally, the process 1000 advances to stage 1008 where
the data
and report information is stored in reporting database 208C for further use
and reference,
exported to a third party reporting system, or otherwise made available for
query,
augmentation, and/or data profile modification and definition.
VIII. Definition and Use of Triggers
As noted earlier, the data collection processes performed in connection with
the
network and associated target devices involve the use of certain events,
network
conditions, trends, data points, and thresholds as a basis for the performance
of other
actions, such as generation, download or refinement of a data collection
profile. In
addition, embodiments of the invention provide for the definition and use of
various types
of triggers in conjunction with data collection profiles.
In the exemplary einbodiment, a trigger is one or more conditions defined
during
an integration process with wireless device 400. Triggers enable SQC 402 to be
invoked
for the purpose of additional metric processing. Each trigger is associated
with a specific
identifier and defines a specific set of states that are visible to wireless
device 400
software. When the SQC functionality is invoked, the trigger identifier is
compared
against triggers included in the downloaded profiles to determine the proper
course of
action. As such, inclusion of a trigger in a specific data collection profile
effectively
defines the conditions under which that data collection profile is to take a
specified
action.
In the exemplary embodiment, triggers may be included in the data collection
directives of a data collection profile, and their inclusion causes SQC to
initiate, abort,
and terminate data collection activity as appropriate when the associated
trigger condition
is invoked by the wireless device 400. An alternative embodiment of triggers
and data
collection functionality is discussed later in section IX. A trigger
invocation that matches
the initiating trigger causes data collection activity to begin. A match of
the terminating
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trigger causes the data collection activity to end, and a inetrics package is
then prepared
for uploading. An abort trigger causes data collection activity to cease, and
a metrics
package is not prepared. In the example used earlier, initiation of an instant
connect
communication caused the SQC to be invoked with an "instant connect
communication
start" trigger event, which is matched against triggers in downloaded profiles
and causes
1o data collection activity to begin on the originating device. Receipt by the
originating
device of the 408 error would cause another trigger to be activated, and the
SQC would
match the event to a terminating trigger in the profile, cause data collection
to stop and a
metrics package to be prepared and uploaded. As can be seen, the inclusion of
a trigger
in a profile effectively selects the condition under which a specific action
associated with
that profile is to be executed. The trigger is not strictly within the
profile, rather it
associates specific profile actions (start, stop, abort) with a specific event
on the device.
In another example, a trigger event may be the initiation of a voice call. In
this
case, commencement of a voice call is the initiating trigger invocation that
causes the
SQC to execute the data collection rules contained in the data collection
profile resident
on the device engaged in the voice call. In this example, the data collection
profile
associated the act of ending the voice call with termination of the data
collection activity,
and may also cause preparation of the metrics package for upload to the
metrics collector.
This data collection activity allows recordation of the metric activity
specified for a call,
and generation of a metrics package associated with each call occurring on the
device.
The use of triggers provides for finely tuned data collection activity. By
linking
profile actions to events defined on the device, substantially any event can
be effectively
measured, including measurements leading up to it and trailing it in time.
Consequently,
iinportant trend information and other indicators embodied in the collected
data can be
quickly identified and exploited, thereby enhancing the quality and usefulness
of
collected data. Any of a variety of triggers may be defined and employed.
Accordingly,
the scope of the invention should not be construed to be limited to any
particular type,
number, combination, implementation or use, of triggers. Details concerning
some
triggers are provided below.
A basic form of one such trigger involves the definition or specification of a
certain occurrence that causes the SQC to be invoked. As used herein, the term
"occurrence" extends to occurrences or non-occurrences of specified things
that define a
specific identity of a trigger. When a determination has been made by the SQC
that the
defined occurrence has happened (for example by being invoked by the wireless
device
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software with the specified trigger identity) or has failed to happen within a
set
timeframe, then one or more data collection activities may be performed by the
SQC. In
addition, the SQC can define certain metrics in certain states to cause
invocation of a
specified trigger identity. Substantially any metric in any state, or any
sequence of
metrics can be defined as causing invocation of a specific trigger identity.
For example,
the a threshold trigger can be invoked by a monitored parameter that exceeds
or falls
below a particular threshold for a defined period of time, which can range
from zero to an
arbitrarily large number. One specific example is a threshold trigger that
fires when a
frame error rate metric exceed a predetermined value.
The trigger identities can be included in data collection profiles, and cause
an
associated action to occur. For example, to define a data collection profile
that results in
a metrics package with information about dropped voice calls, but that does
not collect
information about any other types of calls (successful or blocked), the
following trigger
associations could be used:
Initiate Trigger: Voice Call Start
Terminate Trigger: Voice Call Terminate Blocked
Abort Trigger: Voice Call Terminate
In this example, the terminate trigger causes data capture to cease and a
metrics
package to be prepared, since data collected in relation to this trigger is
the goal of the
collection activity. The abort trigger indicates to the SQC that data
collection should
terminate but no metrics package should be prepared, since the data associated
with this
activity is not the focus of the collection goal.
A related type of trigger is a "domino" trigger, which is activated when a
command is sent from SQP 202 to the SQC residing on the network node. In the
example
previously set forth in which 408 errors are being monitored, the terminating
device in the
example was una*are of the attempted communication session by the originating
device,
so a data collection activity would not have been triggered on the terminating
device in
this case. To ensure that important data related to the conditions surrounding
the
terminating device during the communication attempt is captured, a "domino"
trigger is
used. As illustrated above in the example regarding the 408 TIMEOUT message, a
domino trigger occurs when SQP 201 causes a command, in the form of an SMS or
other
message type, to be sent to the SQC 402 on the terminating device, which
causes an
initiating trigger to activate, and an "on demand" data collection activity
commences
and/or a metrics package is prepared for upload. As part of the "on-demand"
data
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collection activity, metrics may be selected from those existing in the buffer
of the
terminating device and other metrics may be gathered to complete the metrics
package.
In particular, in this example a data collection profile previously activated
on the
terminating device may cause the collection of data that is useful for the "on-
demand"
data collection activity at hand; allowing the domino trigger to gather data
that was
already being collected on the terminating device prior to the arrival the
domino trigger.
The metrics package may be uploaded immediately upon preparation, or at some
other
time specified in the data collection profile.
With reference to Figure 9, details concerning one example of a process,
denoted
at 1100, for data collection is illustrated. The process 1100 begins at stage
1102 where
the SQC 402 on a wireless device, or devices, receives a data collection
profile that
specifies triggers. The triggers specified in the data collection profile may
be configured
so as to direct the SQC 402 to perform data collection activities upon
invocation of the
specified trigger. In the illustrated case, the SQC 402 on the wireless device
engages in a
monitoring process, at stage 1104, to identify activation of a trigger
specified in the data
collection profile. When the initiating trigger is activated, data collection
begins. Once
data collection begins, some or all of the monitored data may either be
collected or it may
be ignored, depending on the instructions contained in the data collection
profile.
In the illustrated process, after an initiating trigger causes data collection
to begin,
data collection proceeds in accordance with instructions contained in the data
collection
profile until an abort or terminating trigger is detected at decision point
1106. For
example, data collection instructions could specify a sampling of data at
periodic intervals
for a specified period of time. Data collection ceases when an abort or
terminating trigger
is activated.
Triggers can be defined that utilize any aspect of wireless device state in
their
impt'ementation. By this mechanism, complex dependencies such as only
collecting data
when certain services are in certain states can be implemented. In a previous
example,
only collecting data for IP data calls made by the instant connect application
can be
implemented as a specific trigger definition which would only activate under
the specific,
constrained set of conditions.
Directing attention finally to Figure 10, details are provided concerning a
process
1300 involving the definition and use of a domino-type trigger. In the
illustrated case, the
process 1300 is perfornzed from the perspective of the communications network.
This
arrangement affords the ability for network personnel to look at and evaluate
an entire
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transaction between wireless devices of the communications network, rather
than
focusing solely on the portion of a transaction associated with a particular
wireless
device.
The process 1300 commences at stage 1302 where one or more metrics packages
are received fiom one or more target wireless devices or other network nodes.
Such data
1o generally concerns one or more parameters of the communications network
and/or
associated wireless devices. The process 1300 then advances to a decision
point at stage
1304 where a determination is made as to whether or not the received data in
the metrics
package(s) implicates another, "non-reporting" network node, such as a
tenninating
device that is unaware that an originating device has attempted to communicate
with it.
If no other network node is implicated, the process 1300 proceeds to stage
1306, wherein
further analysis may be performed.
If, on the other hand, the received data indicates that a "non-reporting"
network
node is implicated and may be able to contribute data that is important to the
analysis of
the transaction, the process 1300 instead advances to stage 1308. At this
stage, SQP 201
causes a command to be sent to the "non-reporting", implicated network node.
In this
case, the command sent from SQP 201 is interpreted as a trigger that enables
the
implicated, non-reporting network node to collect the relevant data and send
the data in a
metrics package.
Thus, if a wireless device "A" sends a page to wireless device "B," but
receives
no response, wireless device "A" receives an error which activates a trigger
that causes a
metrics package to be uploaded to the metrics collector. However, because
wireless
device "B" may not be aware that the page was sent, the wireless device "B" is
unaware
of any error or problem having occurred, and would not have been triggered to
upload a
metrics package associated with the error. Accordingly, consideration of the
entire
transaction, or attempted transaction, between devices "A" and "B" is
necessary to
achieve a fuller understanding and appreciation of the problem.
At stage 1308 SQP 201 causes a command to be sent to wireless device "B". At
stage 1310 the command is interpreted as an initiating trigger that in turn
causes a data
collection activity to occur, such as selection of metrics from the buffer of
device "B",
collection of any additional metrics needed, and preparation and upload of a
metrics
package. Next, the metrics package from wireless device "B" is received by the
metrics
collector at stage 1312, and additional analysis may be performed. At this
stage, metrics
packages uploaded by such other network devices in connection with the data
collection
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profile are received and analyzed. The process 1300 may be performed once or
repeatedly as part of an iterative analysis and resolution process.
IX. Scripted Device Profiles
In another embodiment of the invention, a, scripted device profile, rather
than a
data collection profile, is used to direct processing of metrics generated by
the target
device. In this embodiment, instead of a limited set of fixed functions, the
SQC is
"scripted" with a fully functional programming language, allowing any
algorithm for
metric, trigger, and measurement handling to be defined by the scripted device
profile.
The additional flexibility significantly increases the number of scenarios
that the data
collection and management system of the invention can address because it
allows even
more of the details of metric collection, processing and management to be
dynamically
defined by the scripted device profile download rather than being coded into
the SQC.
In this embodiment and in contrast to the previous embodiment, when metrics
are
generated as a result of an activity or transaction performed on the target
device as
previously described, metric processing, rather than being limited to
collecting the metric,
not collecting the metric, or causing invocation of a specified trigger
identity, is
significantly more flexible. -More specifically, this embodiment of the
invention allows
complex processing on metric collection to be entirely defined by the
downloaded
scripted device profile. Metrics parameters and triggered functionality, which
replace the
data collection directives (rules and triggers) described in the previous
embodiment, are
defined in the scripted device profile and govern the processing of metrics.
As before, the
service quality client (SQC) is responsible for receiving and otherwise
managing profiles.
With reference to Figure 11, when a metric is generated on the wireless device
400, the SQC 403 is invoked which causes metrics processing element 404A to
consult
with metric parameters 404B specified in scripted device profile 404 to
determine the
proper handling of the metric. In many cases, no information is available in
metric
parameters 404A concerning the metric, so the metric is ignored, device
operation
continues, and metrics continue to be generated as part of the noimal
operation of
wireless device 400.
However, if metric parameters 404A do specify handling of the metric,
additional
processing is then performed. The additional processing can take one of two
forms. In
the first form called filtering 404C, the metric is compared against
parameters specified in
metric parameters 404B. The parameters specify both the type of comparison and
the
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values necessary for the comparison. As a result of this comparison a binary
decision is
made about whether the metric should be placed in one or more buffers 406 or
ignored.
The specific comparisons available are defined as part of the SQC
implementation, and
substantially any sort of comparison could be performed. Comparisons specified
in
metric parameters 404B may include simple binary decisions, such as "always
collect this
1o metric", or "collect if this metric meets this binary or numeric
comparison." Other
comparisons may include comparison of the metric with another metric or with
another
aspect of the wireless device 400 state. Even more complex comparisons
involving
multiple criteria and "pre-processing" to determine if a particular result has
been achieved
may be specified in the metric parameters. In general the comparisons
specified in metric
parameters 404B can be substantially any software functionality, but may also
be limited
to a relatively small number of commonly used actions defined at the time the
SQC is
implemented.
Having met criteria specified in the scripted device profile 404, the metric
will be
collected in one or more buffers 406. As in the previous embodiment, the
common
functions are fixed sized buffers for a specific number of metrics, with a
simple rotating
buffer model where a new metric may overwrite the oldest stored metric if the
buffer is
full. Other policies can include invoking triggered functionality 404D
(discussed further
below) if the buffer is full and a prioritized buffer where metrics collected
under certain
conditions overwrite metrics collected under different conditions.
Substantially any
buffer management model can be implemented in conjunction with the invention
and
specified as part of metric parameters 404B. In practice, a limited set of
fixed functions
may be implemented, and additional algorithms may be implemented as triggered
functionality 404D. It should be noted that in some cases, the metric may be
included in
a metrics package without first having been buffered.
The second form of metric processing also utilizes the comparison
functionality
described, but instead of collecting the metric upon a positive result as
defined for
filtering, a previously downloaded script, referred to herein as triggered
functionality
404D is invoked to direct further metric processing.
Triggered functionality 404D is a significant departure from the previous
embodiment of trigger and data collection profile functionality. Triggered
functionality
404D is a full-featured computer language, i.e., it is software that directs
the actions of
the wireless device 400 processor, so any software functionality can be
implemented on
the wireless device 400 in connection with data collection, management and
analysis. As
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a result of being invoked by a metric comparison, triggered funetionality 404D
assumes
control of metric processing. As previously noted, triggered functionality can
perform
substantially any software function on wireless device 400, and it has access
to the
invoking metric, all of the buffers in which metrics may be stored, additional
state
information on the device, metric packages, and upload functionality. In the
previous
embodiment which utilized data collection profiles and triggers, there was a
limited set of
actions that could be executed in response to a trigger invocation, and the
triggers each
had defined functions that were performed in response to their activation. In
this
embodiment, use of scripted device profiles and triggered functionality allows
the result
of any metric comparison as defined above to act as a trigger, and allows
complete
flexibility as to the subsequent action performed (the "triggered
functionality") after a
trigger is activated. More specifically, triggered functionality 404D can
cause generation
of new metrics, and it can modify metrics parameters 404B to change the
criteria and
processing directives contained in the scripted device profile 404. Triggered
functionality
404D can further copy, modify and otherwise process buffer 406 contents and
can
transform the resulting data into metrics packages 408 for later upload. The
triggered
functionality can ,perform uploads and cause new scripted device profiles or
other
software code to be downloaded to wireless device 400 and executed thereon.
Triggered fiinctionality 404D is contained within the scripted device profile
404 in
this embodiment. Any of a number of models known in the art for enabling a
software
downloadable model on wireless device 400 can be prove effective as a
management
model for triggered functionality 404D. These models include virtual machines
(as
implemented by Java for example) and actual machine language (as implemented
by the
BREW environment for example) running in a prescribed environment. In
addition,
numerous commercial packages are available today to perform "over the air"
firmware
upgrade"s, effectively allowing any software to be downloaded and added to the
existing
software on wireless device 400 and subsequently be invoked as triggered
functionality.
As a complete computer language, triggered functionality 404D can implement
virtually any software functionality possible on the device. In this
embodiment, the
triggered functionality 404D is implemented in native device code, so it has
access to all
state and functionality of the wireless device 400. However, certain
implementations may
have more limited access to device state and functionality and still perform
substantially
the same role.
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In addition to the triggered functionality that is invoked by metric
comparisons, a
set of special events on wireless device 400 are defined as special triggers
412 and can
similarly invoke triggered functionality 404D. Amongst others, when a scripted
device
profile 404 is first downloaded to wireless device 400, a special trigger 412
activates
triggered functionality 404D to execute profile start up - in some cases to
configure
l0 triggers and metric parameters. When wireless device 400 is powered on or
off, reset, or
a processor exception occurs, a special trigger 412 is activated. These
special triggers
may be implemented to cause triggered functionality to be invoked by such
actions as
application invocation, user actions or other activities that would not
otherwise naturally
cause generation of metrics. Special triggers 412 may be invoked by
substantially any
other event on the device that may prove of interest for later analysis.
Because of the general nature of the capability of the triggered functionality
404D,
many other aspects of the data collection functionality (such as abort
triggers or
termination triggers) become different triggered functions rather than special
functions.
As noted earlier, the scripted embodiment of SQC discussed in this section
allows
complete flexibility of what actions, if any, are taken when one of these
events occurs,
significantly increasing the number of interesting measurements that can be
effectively
performed by the data collection and management system of the invention.
X. Telecommunication Devices and Computing Environments
As indicated herein, enibodiments of the present invention may be implemented
in
connection with a special purpose or general purpose telecommunications
device,
including wireless and wireline telephones, other wireless communication
devices, or
special purpose or general purpose computers that are adapted to have
comparable
telecommunications capabilities. Embodiments within the scope of the present
invention
also include computer-readable media for carryirig or having computer-
executable
instructions or electronic content structures stored thereon, and these terms
are defined to
extend to any such media or instructions that are used with telecommunications
devices.
By way of example such computer-readable media can comprise RAM, ROM,
flash memory, EEPROM, CD-ROM or other optical disk storage, magnetic disk
storage
or other magnetic storage devices, or any other medium which can be used to
carry or
store desired program code in the form of computer-executable instructions or
electronic
content structures and which can be accessed by a general purpose or special
purpose
computer, or other computing device.
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When information is transferred or provided over a network or another
communications connection (either hardwired, wireless, or a combination of
hardwired or
wireless) to a computer or computing device, the computer or computing device
properly
views the connection as a computer-readable medium. Thus, any such a
connection is
properly termed a computer-readable medium. Combinations of the above should
also be
included within the scope of computer-readable media. Computer-executable
instructions
comprise, for example, instructions and content which cause a general purpose
computer,
special purpose computer, special purpose processing device or computing
device to
perform a certain function or group of functions.
Although not required, aspects of the invention have been described herein in
the
general context of computer-executable instructions, such as program modules,
being
executed by computers in network enviroinnents. Generally, prograni modules
include
routines, programs, objects, components, and content structures that perform
particular
tasks or implement particular abstract content types. Computer-executable
instructions,
associated content structures, and program modules represent examples of
program code
for executing aspects of the methods disclosed herein.
The described embodiments are to be considered in all respects only as
exemplary
and not restrictive. The scope of the invention is, therefore, indicated by
the appended
claims rather than by the foregoing description. All changes which come within
the
meaning and range of equivalency of the claims are to be embraced within their
scope.
