Patent Description:
Network and customer experience monitoring solutions are widely accepted standards for the operations of carrier service provider networks across both fixed networks (e.g., Cable/Multi System Operator (MSO), IP broadband such as Digital Subscriber Line (DSL), Fiber To Home (FTTH), etc.) and mobile networks (e.g., second and a half generation (<NUM>), third generation (<NUM>), fourth generation (<NUM>), 3GPP Long Term Evolution (LTE), etc.). These systems monitor network traffic via probe devices, then process that traffic through a variety of stages to derive actionable information as it pertains to subscriber experience (quality of service, quality of experience), subscriber behavior (application usage, service usage, etc.), subscriber location, etc. In practice, actionable information may refer to statistical indicators (typically referred to as Key Performance Indicators or KPIs) that are computed from source data processed by the probes, and then made available to various different user constituents at the carrier for the purpose of driving their business process.

Contemporary telecommunication network environments typically involve multiple technologies, multiple protocols, and interconnections to a wide variety of networks. More complex network environment means that the potential for problems in internetworks is high, and the source of problems is often elusive. Thus, there is a strong demand for robust diagnostic tools for troubleshooting networking failures.

Currently, there are performance monitoring tools which correlate multiple protocols by correlating Protocol Data Units (PDUs) across several different interfaces and protocols into a single session record that can be viewed in an analyzer tool. While such tools are useful in identifying certain network issues, at any given moment, there may be several hundreds or even thousands of PDUs that need to be analyzed over a short period of time. Thus, existing monitoring tools are limited in their diagnostic capabilities since in order to identify a root cause of any failure it is necessary to manually sift through all the transactions, PDUs and causes. This is very time consuming.

It is to be appreciated that when a network problem arises, it can be rooted anywhere in the networks. To troubleshoot network issues quickly, it is imperative to have automated analysis scheme capable of identifying a root cause for each network issue.

<CIT> is directed, in general, to data monitoring, and, more particularly, to systems and methods for monitoring over-the-top adaptive video streaming; <CIT> relates to a computer program and monitoring apparatus; <CIT> relates to methods and systems for performing root cause analysis.

Aspects of the invention are in accordance with the appended claims. The purpose and advantages of the illustrated embodiments will be set forth in and apparent from the description that follows. Additional advantages of the illustrated embodiments will be realized and attained by the devices, systems and methods particularly pointed out in the written description and claims hereof, as well as from the appended drawings.

In accordance with a purpose of the illustrated embodiments, in one aspect, a network monitoring system is provided according to the appended claims.

Rules associated with session data of a plurality of transactions in the wireless communication system are generated. One or more failures in the wireless communication system are identified. One or more transactions from the plurality of transactions associated with the identified failures are identified. One or more network elements of the wireless communication system substantially responsible for the identified failures are identified by correlating the transactions based on the generated rules.

The accompanying appendices and/or drawings illustrate various, non-limiting, examples, inventive aspects in accordance with the present disclosure:.

The below illustrated embodiments are directed to a system and method for multi cause correlation in wireless protocols in which a component or a feature that is common to more than one illustration is indicated with a common reference. It is to be appreciated the below illustrated embodiments are not limited in any way to what is shown, as the illustrated embodiments described below are merely exemplary of the invention, which can be embodied in various forms, as appreciated by one skilled in the art. Therefore, it is to be understood that any structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative for teaching one skilled in the art to variously employ the present invention. Furthermore, the terms and phrases used herein are not intended to be limiting but rather to provide an understandable description of the illustrated embodiments.

Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present invention, exemplary methods and materials are now described.

It must be noted that as used herein and in the appended claims, the singular forms "a", "an," and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a stimulus" includes a plurality of such stimuli and reference to "the signal" includes reference to one or more signals and equivalents thereof known to those skilled in the art, and so forth.

It is to be appreciated the embodiments of this invention as discussed below are preferably utilized in conjunction with a software algorithm, program or code residing on computer useable medium having control logic for enabling execution on a device having a computer processor. The device typically includes memory storage configured to provide output from execution of the computer algorithm or program. As used herein, the term "software" is meant to be synonymous with any code or program that can be in a processor of a host computer, regardless of whether the implementation is in hardware, firmware or as a software computer product available on a disc, a memory storage device, or for download from a remote machine. The embodiments described herein include such software to implement the equations, relationships and algorithms described below. One skilled in the art will appreciate further features and advantages of the certain embodiments described herein. Thus, the certain embodiments are not to be understood to be limited by what has been particularly shown and described, except as indicated by the appended claims.

In exemplary embodiments, a computer system component may constitute a "module" that is configured and operates to perform certain operations as described herein below. Accordingly, the term "module" should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired) or temporarily configured (e.g. programmed) to operate in a certain manner and to perform certain operations described herein.

<FIG> illustrates a block diagram of a network monitoring system. As illustrated, mobile devices <NUM> and <NUM> may be capable of transmitting and receiving data (e.g., web pages, audio, video, etc.) to and from each other over network <NUM>. Also, web server <NUM> may be configured to provide one or more web pages to client device <NUM> through network <NUM>. In various embodiments, network <NUM> may include any suitable wireless/mobile computer or data network including, for example, a <NUM>, <NUM>, or LTE wireless networks, etc..

Communications between mobile devices <NUM> and <NUM>, as well as communications between web server <NUM> and client device <NUM>, may be monitored by network monitoring system <NUM>, as data packets comprising those communications pass through wireless network <NUM> spanning multiple interfaces.

As such, network monitoring system <NUM> may include a network monitor or analyzer, a packet sniffer, a probe, or the like, coupled to network <NUM>. Protocols used to enable communications taking place in <FIG> may be selected, for instance, based upon the type of content being communicated, the type of wireless network <NUM>, and/or the capabilities of devices <NUM>, <NUM>, and/or <NUM>. Examples of types of protocols that may be used include, but are not limited to, HTTP, Real Time Messaging Protocol (RTMP), and RTP.

Each communication session for the various devices <NUM>, <NUM>, and/or <NUM> may have different start and stop times, and may be subject to different network traffic constraints. During each session, the available bandwidth for that session may change multiple times. Also, a data stream may start and stop during a given session.

Accordingly, network monitoring system <NUM> may be configured to sample (e.g., unobtrusively) related data packets for a communication session in order to track the same set of user experience information for each service, each session and each client without regard to the protocol used to support the session. Various embodiments of the present invention further contemplate that network monitoring system <NUM> can optionally further provide other services, such as, but not limited to, an analysis scheme whereby all relevant information related to a subscriber activity spanning multiple interfaces is examined to provide precise root cause failure identification of the session. Generally speaking, such analysis scheme may utilize a rules engine to create a standard set of cause analysis rules which will be used by an analyzer module coupled to the rules engine to determine the source of the failure and can be further tuned to meet individual customer needs.

According to some embodiments, network monitoring system <NUM> may be configured to automatically sift through and correlate relevant transactions and corresponding failure causes to automatically discover the actual network element and transaction that caused the identified failure. A myriad of transactions can spawn multiple error messages into subscriber session records. For example, a failure of a particular interface can cause multiple error messages to appear in different subscriber session records that represent the output of various wireless network transactions, thereby creating interleaved sequences of events in the respective subscriber session records. Examples of the technology disclosed herein lead to automation in leveraging all relevant information related to a subscriber activity for tasks such as automated problem troubleshooting of End-to-End (E2E) services and/ or visualization of the information in the subscriber session records. Such automation inherently saves time and man hours and helps solve user problems that a particular target network element may be experiencing. Automated troubleshooting systems can benefit greatly from identification and representation of groups of related causes, as opposed to individual error messages, as this reduces noise (i.e., erroneous, meaningless, missing, incomplete, or difficult-to-interpret information), compresses the data and facilitates a more accurate representation of all transactions in the wireless network.

Generally speaking, client devices <NUM>, <NUM>, and <NUM> may include any computer system or device such as, for example, a personal computer, laptop computer, tablet computer, mobile device, smart phone, network-enabled devices, web-enabled televisions, and the like. Client devices <NUM>, <NUM>, and <NUM> may allow users to carry out voice communications, navigate the Internet or other data networks using a web browser application or the like via a Graphical User Interface (GUI), etc. Additionally or alternatively, client device <NUM> may access a content catalog made available by web server <NUM> through a stand-alone or web-based client application. Web server <NUM> may include any server or computer system capable of delivering content to device <NUM>.

Although only four devices <NUM>, <NUM>, <NUM>, and <NUM> are shown in <FIG>, it will be understood wireless network <NUM> may comprise any number of elements (i.e., nodes and endpoints). For example, in some implementations, wireless network <NUM> may include nodes or endpoints that may be components in a <NUM> or <NUM> wireless network, such as a Serving General Packet Radio Service (GPRS) Support Node (SGSN), Gateway GPRS Support Node (GGSN) or Border Gateway in a GPRS network, Packet Data Serving Node (PDSN) in a Code Division Multiple Access (CDMA) <NUM> network, a Mobile Management Entity (MME), eNodeB, Serving Gateway (SGW), Home Subscriber Server (HSS) in a LTE network or any other core network nodes or routers that transfer data packets or messages between endpoints. Moreover, it will be understood that such nodes and endpoints may be interconnected in any suitable manner, including being coupled to one or more other such nodes and/or endpoints.

As noted above, many packets traverse wireless network <NUM> between endpoints. These packets may represent many different sessions and protocols. For example, if mobile device <NUM> is used for a voice or video call, then it may exchange Voice over Internet Protocol (VoIP) or Session Initiation Protocol (SIP) data packets with a SIP/VoIP server (not shown) using RTP. If mobile device <NUM> is used to send or retrieve email, it may exchange Internet Message Access Protocol (IMAP), Post Office Protocol <NUM> Protocol (POP3), or Simple Mail Transfer Protocol (SMTP) messages with an email server (not shown). If client device <NUM> is used to download or stream video, it may use Real Time Streaming Protocol (RTSP) to establish and control media sessions with web server <NUM>. Alternatively, the user at mobile devices <NUM> and <NUM> or client device <NUM> may access a number of websites using HTTP protocol to exchange data packets with web server <NUM>. It will be understood that packets exchanged between devices may conform to numerous other protocols now known or later developed.

In a typical situation, approximately one percent of the packets traversing wireless network <NUM> carry control data, such as information for setting-up, managing or tearing-down calls or sessions between endpoints. The other ninety-nine percent of the packets carry user data, such as actual voice, video, email or information content to and from connected devices.

In various embodiments, network monitoring system <NUM> may be used to monitor the performance of wireless network <NUM>. To that end, monitoring system <NUM> may be configured to capture packets that are transported across wireless network <NUM>. In some embodiments, packet capture devices may be non-intrusively coupled to network links to capture substantially all of the packets transmitted across the links. It will be understood that, in an actual network, there may be dozens or hundreds of physical, logical or virtual connections and links between nodes. In some cases, network monitoring system <NUM> may be coupled to all or a high percentage of these links. In other embodiments, monitoring system <NUM> may be coupled only to a portion of wireless network <NUM>, such as only to links associated with a particular carrier or service provider. The packet capture devices may be part of network monitoring system <NUM>, such as a line interface card, or may be separate components that are remotely coupled to network monitoring system <NUM> from different locations.

Monitoring system <NUM> may include one or more processors running one or more software applications that collect, correlate and/or analyze media and signaling data packets from wireless network <NUM>. Monitoring system <NUM> may incorporate protocol analyzer, session analyzer, and/or traffic analyzer functionality that provides OSI (Open Systems Interconnection) Layer <NUM> to Layer <NUM> troubleshooting by characterizing network traffic by links, nodes, applications, service types and servers on wireless network <NUM>. In some embodiments, these operations may be provided, for example, by the IRIS® toolset available from NetScout Inc. , although other suitable tools may exist or be later developed. The packet capture devices coupling network monitoring system <NUM> to wireless network <NUM> may be high-speed, high-density probes that are optimized to handle high bandwidth IP traffic, such as the GEOPROBE® G10, also available from NetScout, Inc. , although other suitable tools may exist or be later developed. A service provider or network operator may access data from monitoring system <NUM> via a user interface station having a display or graphical user interface, such as the IRISVIEW configurable software framework that provides a single, integrated platform for several applications, including feeds to customer experience management systems and operation support system (OSS) and business support system (BSS) applications, which is also available from NetScout, Inc. , although other suitable tools may exist or be later developed.

Monitoring system <NUM> may further comprise an internal or external memory for storing captured data packets, user session data, and configuration information. Monitoring system <NUM> may capture and correlate the packets associated with specific data sessions. In some embodiments, related packets may be correlated and combined into a record for a particular flow, session or call on wireless network <NUM>. These data packets or messages may be captured in capture files. A call trace application may be used to categorize messages into calls and to create Call Detail Records (CDRs). These calls may belong to scenarios that are based on or defined by the underlying network. In an illustrative, non-limiting example, related packets can be correlated using a <NUM>-tuple association mechanism. Such a <NUM>-tuple association process may use an IP correlation key that includes <NUM> parts: server IP address, client IP address, source port, destination port, and Layer <NUM> Protocol (Transmission Control Protocol (TCP), User Datagram Protocol (UDP) or Stream Control Transmission Protocol (SCTP)).

As the capability of wireless network <NUM> increases toward <NUM> Gigabits/second (Gbps) and beyond (e.g., <NUM> Gbps), however, it supports more services, users' flows and sessions. As such, it becomes difficult for a service provider or network operator to analyze all the traffic across entire wireless network <NUM>, for example, to identify problem nodes or links. Some systems may collect all the data for a relatively short period of time, hoping that the sample taken is representative. However, as noted above, even such sample corresponding to a short period of time may include hundreds of PDUs. Other systems may collect a percentage of network traffic all the time and attempt to extrapolate the data for the entire network by simply scaling it. However, such selective collection of data may complicate troubleshooting diagnosis process. To address these and other concerns, certain systems and methods described herein may enable the adaptive monitoring of telecommunications networks.

Turning now to <FIG>, a block diagram of a network monitoring software program is depicted. In some embodiments, network monitoring software <NUM> may be a software application executable by monitoring system <NUM> of <FIG>. As previously noted, a plurality of communication sessions or data streams may be transmitted across wireless network <NUM> between devices <NUM>, <NUM>, <NUM>, and/or <NUM>. Such communications may be streamed over HTTP, RTMP, RTP, or any other suitable protocols.

Monitoring probe <NUM> may be configured to capture data packets from wireless network <NUM>, including, for example, data from one or more HTTP requests or sessions. As such, monitoring probe <NUM> may determine subscriber identifying information for the captured data packets and may combine related data into session or request records. Monitoring probe <NUM> may then feed session records and captured packet data to monitoring engine <NUM>. In some cases, a session record may include multiple segments that are provided to monitoring engine <NUM> periodically while an associated session is active. Monitoring engine <NUM> may in turn be configured to extract session data from each session record and to identify the protocol for each session record.

Session data may include a plurality of PDUs corresponding to a plurality of different protocols stored to database <NUM>. In other words, the plurality of PDUs comprises a plurality of signaling messages exchanged between one or more elements of wireless communication system <NUM>. Database <NUM> may also store subscriber information and client device data.

Network monitoring software <NUM> may allow the service provider for wireless network <NUM> to collect data from various HTTP requests or sessions concurrently or simultaneously. Data for multiple requests or sessions is stored in database <NUM>, which allows the service provider to track each service or to extract system-wide parameters. For example, monitoring probe <NUM> and/or monitoring engine <NUM> may identity the type of protocol being used for each session by analyzing the header of one or more data packets for that session.

Monitoring probe <NUM> and/or monitoring engine <NUM> may also track the bandwidth available to each service session, and may identify bandwidth changes that occur in real-time. Moreover, monitoring probe <NUM> and/or monitoring engine <NUM> may detect when gaps or missing fragments occur in the stream of data packets for any of the requests or sessions. The requests or service parameters, bandwidth information, and gap data may be collected to database <NUM> and/or presented to the service provider.

At least in some embodiments, session monitoring module <NUM> may use the collected information to generate QoE and KPIs for E2E service and for the overall network. The KPIs may be based, for example, on how often re-buffering, screen resolution changes, gaps, and/or missing fragments are detected. Excessive buffering during the session (i.e. re-buffering), numerous screen resolution changes, and gaps in the service stream may lower a user's QoE.

In an embodiment of the present invention, different sets of cause rules may apply to different types of traffic. Each rule may in turn dictate a portion of that traffic that will be used in subsequent processing such as, for example, the analysis of various individual transactions based on a specific rule and/or ruleset or the like. Additional examples of utilized transactional data may include, but are not limited to, connection establishment indicators, service performance indicators, authentication indicators, network congestion indicators, connection maintenance indicators, service completion indicators, service quality indicators, and/or service availability indicators.

Network monitoring system <NUM>, under control of software <NUM>, may also be configured to aggregate data to enable backhauling, to generate netflows and basic KPI calculations, time stamping of data, port stamping of data, filtering out unwanted data, protocol classification, and deep packet inspection (DPI) analysis. In addition, network monitoring system <NUM>, may be further configured to perform analysis of data, extraction of key parameters for call correlation and generation of call data records (CDRs), application specific processing, service specific processing, etc..

According to an embodiment of the present invention, network monitoring software <NUM> also includes a rule engine <NUM>. Rule engine <NUM> includes one or more software modules or components that manages and automates the aforementioned cause rules. For instance, rule engine <NUM> evaluates and fires one or more of the rules based on the evaluation of particular data. Generally, one advantage of a rule engine is the separation of the rules from the underlying application code. With the rules separated from the application code, rule engine <NUM> allows the users to modify the rules frequently without the help of technical staff and hence, allowing network monitoring software <NUM> to be more adaptable with the dynamic rules. The cause rules may be grouped or partitioned into one or more rule sets, where each rule set contains one or more rules. Then rule engine <NUM> executes the rules according to the execution order. In one embodiment, a model of the execution order is generated and loaded into rule engine <NUM>.

Rule engine <NUM> may also be configured to exchange information with a root cause analyzer <NUM> as described below with respect to <FIG>. The exemplary root cause analyzer <NUM> of <FIG> analyzes the data, parameters and/or information collected by the monitoring probes <NUM> (e.g., transactions, causes) based on an appropriate rule/ruleset to determine and/or identify the root cause(s) of network performance problems.

Referring now to <FIG>, a flowchart of a method for of automatically identifying failures in wireless networks using multi cause correlation is provided, in accordance with embodiments of the present invention. Before turning to description of <FIG>, it is noted that the flow diagram in <FIG> shows examples in which operational steps are carried out in a particular order, as indicated by the lines connecting the blocks, but the various steps shown in this diagram can be performed in any order, or in any combination or sub-combination. It should be appreciated that in some embodiments some of the steps described below may be combined into a single step. In some embodiments, one or more steps may be omitted. In some embodiments, one or more additional steps may be performed. As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a method or computer program product. In some embodiments, the method described below may be performed, at least in part, by one or more components of network monitoring system <NUM>.

According to an embodiment of the present invention, at step <NUM>, monitoring engine <NUM> may provide on demand activation of the automated network failure root-cause analysis. In some embodiments, proactive service assurance can aid in lowering the impact and the prevention of failures or outages on communications network. In one embodiment, one or more network failures may be automatically detected based on data collected by monitoring probes <NUM>. For example, monitoring probes <NUM> can collect network data indicating one or more network failures (e.g., alarms and/or traps) by monitoring one or more network elements or systems of wireless network <NUM>. In an alternative embodiment, one or more network failures may be identified by a user while evaluating a plurality of subscriber session records stored in database <NUM> for long-term storage.

In certain embodiments, root cause analyzer <NUM> may be configured, at step <NUM>, to dynamically obtain from rule engine <NUM> a rule set related to the one or more network failures identified by monitoring engine <NUM> in step <NUM>. In one embodiment, root cause analyzer <NUM> may identify an appropriate rule set according to any number and/or combination of attributes such as physical interface (e.g. port, slot), network protocol, content source and destination identifiers (e.g., IP addresses), one or more wireless network nodes (e.g., Access Point Name (APN)), interface type (e.g. Ethernet), one or more QoS (Quality of Service) parameters, Layers <NUM> through <NUM> information (e.g. context-dependent, application-level, etc.), any arbitrary header content and/or payload content, session, environmental conditions, and any other type of deep-packet processing information. In some embodiments, each rule set matches one or more transactions with one or more cause codes for a given protocol in the wireless communication system <NUM>.

At least in some embodiments of the present invention, rule engine <NUM> may include a natural language enhanced user interface. As discussed above, rule engine <NUM> broadly refers to a software module that manages cause rules. For instance, some embodiments of the rule engine <NUM> may store cause rules, evaluate cause rules, and execute cause rules based on results of rule evaluation. In some embodiments, one or more rule templates in a natural language are generated from one or more predefined sentences. The predefined sentences can be written in the natural language syntax as well using a plain grammar format. A natural language as used herein generally refers to a language written or spoken by humans for general-purpose communication, as opposed to constructs, such as computer-programming languages, machine-readable or machine-executable languages, or the languages used in the study of formal logic, such as mathematical logic. Some examples of a natural language include English, German, French, Russian, Japanese, Chinese, etc. In some embodiments, the predefined sentences are cause rules previously submitted by users. The predefined sentences may also include rules (e.g., cause rules) and/or sentences provided by administrators of the rule engine <NUM> and/or developers of the rule engine <NUM>. Accordingly, in one embodiment, a user interface of rule engine <NUM> may be created using the rule templates to allow a user to compose rules for rule engine <NUM>.

According to an embodiment of the present invention, in order to perform a root cause analysis, at step <NUM>, root cause analyzer <NUM> is configured to identify one or more transactions associated with the failure(s) identified in step <NUM>. In one embodiment, root cause analyzer <NUM> may be configured to obtain a timestamp that identifies a relative time when the identified failure(s) occurred. This timestamp may be used by root cause analyzer <NUM> to determine which data to read from database <NUM>. The timestamp can also be used in comparisons to other transactions performed at the network <NUM> to determine if dependencies from other transactions are possible, if the transaction might be dependent on another transaction or if conflicting transactions have taken place.

Next, at step <NUM>, once a plurality of transactions relevant to a plurality of identified/detected network failures is identified, root cause analyzer <NUM> performs root cause analysis based on the data associated with the plurality of relevant transactions stored in database <NUM>. <FIG> illustrate a method of performing a root cause analysis of network failures in a multiprotocol wireless communication system, according to an example. Referring now to <FIG>, as noted above, in one embodiment the wireless network <NUM> conforms to the basic architecture of the LTE technology of 3GPP. Under this basic architecture, the wireless network <NUM> comprises at least one User Equipment (UE), at least one eNodeB <NUM>, at least one MME <NUM> and at least one HSS <NUM>. The basic architecture refers to standards that are formulated in accordance with the LTE series technologies, and the LTE series technologies comprise the LTE technology, the LTE-advanced technology and the predecessor technologies of the LTE technology. The predecessor technologies include, for example, a Universal Mobile Telecommunications System (UMTS) or a Global System for Mobile Communications (GSM), etc..

Furthermore, the aforesaid basic architecture may be divided into two parts, namely, an access network and an Evolved Packet Core (EPC). Specifically, the access network comprises the UE and the eNodeB <NUM>, and the EPC comprises the MME <NUM> and the HSS <NUM> as well as at least one Serving Gateway (S-GW) and at least one Packet Data Network Gateway (P-GW). Because the UE, S-GW and the P-GW are not directly related to the illustrated embodiment, they are not depicted in the drawings. Furthermore, basic operations, the communication manner and the connections of the eNodeB <NUM>, MME <NUM>, HSS <NUM>, the S-GW and the P-GW can all be known from the standards formulated in accordance with the LTE series technologies, so only contents directly related to embodiments of the present invention will be described hereinafter.

As shown in <FIG>, the UE enters an attachment procedure with eNodeB <NUM>, MME <NUM> and HSS <NUM>. As part of the attachment procedure, eNodeB <NUM> transmits Non-Access Stratum (NAS) attach request <NUM> to MME <NUM>. To enable proximity services (e.g., direct communication over the radio and/or via another path), the wireless network elements may discover each other. NAS messages, such as NAS attach request <NUM> may be used to communicate discovery between eNodeB <NUM> and MME <NUM>. NAS attach request <NUM> may include various content, which may be used for discovery. MME <NUM> further sends a Diameter- Update Location Request <NUM> towards HSS <NUM>. In response, under normal operation, HSS <NUM> typically sends a Diameter - Update Location Accept to MME <NUM>. However, in certain cases, HSS <NUM> may respond with a Diameter-Update <NUM> having a specific error <NUM>, such as "Unknown EPS subscription" (in the example illustrated in <FIG>) or "Diameter error RAT not allowed" (in the example illustrated in <FIG>). HSS <NUM> sends the former error code when UE's International Mobile Subscriber Identity (IMSI) is known to HSS <NUM>, but the UE user has no EPS subscription. HSS <NUM> sends a later error code to indicate that the radio access technology (RAT) type used by the UE is not allowed for the IMSI.

While specific implementations are discussed herein with respect to a Diameter protocol and specific transactions, it is understood that this is done for illustrative purposes only.

Further, as shown in <FIG>, in both cases, MME <NUM> transmits a reject (connection release) message to the eNodeB <NUM>, and reject message <NUM> can contain a cause value <NUM> indicating the rejected reason. The cause value <NUM> can be "No suitable cells in tracking area", for example. Notably, two different call scenarios (illustrated in <FIG>) trigger different error codes <NUM> on the Diameter Interface. However, these error codes <NUM> map to the same cause value <NUM> included in the reject message <NUM>. In existing networking monitoring tools the reason of the network failure can be determined by analyzing the cause value <NUM> contained in the reject message <NUM>. However, since different network issues could potentially be associated with the same cause value <NUM>, existing monitoring tools are limited in their diagnostic capabilities. In fact in order to identify a real cause of any failure users may be required to manually analyze and correlate the messages between different interfaces. This is very time consuming.

Advantageously, various embodiments of the present invention disclose root cause analyzer module <NUM> that utilizes one or more cause rules to identify network elements and/or transactions that caused the analyzed failure. At least in some embodiments, each rule in the at least one ruleset specifies a timestamp associated with occurrence of the one or more transactions matched with one or more cause codes for each protocol. Table <NUM> below illustrates exemplary rule set for different wireless protocols in accordance with aspects of the present invention:.

Table <NUM> below illustrates another exemplary rule set for a scenario where a failure on the Authentication, Authorization and Accounting (AAA) server results in a cascading series of transaction failures across different interfaces (e.g., S1-MME, S11, S5 and S6b) in accordance with aspects of the present invention:.

Thus, according to an embodiment of the present invention, root cause analyzer <NUM> employs the cause rules to automatically identify failure causes by correlating transactions and corresponding cause codes (cause values) using, for example, timestamps, thusly substantially eliminating the need for any manual analysis. Next, at step <NUM>, root cause analyzer <NUM> displays root cause analysis results to a user via a user interface. Such analysis results may include, for example, information related to the identified network element of the wireless communication system <NUM>.

Advantageously, the disclosed embodiments of the present invention enable exclusively automatic troubleshooting of E2E services. Furthermore, the disclosed embodiments provide network monitoring systems an ability to quickly triage a plurality of identified/detected network problems, which is quite valuable to the end users of such monitoring systems.

Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages.

Aspects of the present invention are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention.

Embodiments of the network monitoring system may be implemented or executed by one or more computer systems. One such computer system, the network monitoring system <NUM> is illustrated in <FIG>. In various embodiments, network monitoring system <NUM> may be a server, a distributed computer system, a workstation, a network computer, a desktop computer, a laptop, or the like.

Network monitoring system <NUM> is only one example of a suitable system and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the invention described herein. Regardless, network monitoring system <NUM> is capable of being implemented and/or performing any of the functionality set forth hereinabove.

Network monitoring system <NUM> is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or configurations that may be suitable for use with the network monitoring system <NUM> include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed data processing environments that include any of the above systems or devices, and the like.

The components of network monitoring system <NUM> may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. Network monitoring system <NUM> may be practiced in distributed data processing environments where tasks are performed by processing devices that are linked through a communications network. In a distributed data processing environment, program modules may be located in both local and remote computer system storage media including memory storage devices.

The network monitoring system <NUM> is shown in <FIG> in the form of a general-purpose computing device. The components of network monitoring system <NUM> may include, but are not limited to, one or more processors or processing units <NUM>, a system memory <NUM>, and a bus <NUM> that couples various system components including system memory <NUM> to processor <NUM>.

Bus <NUM> represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

Network monitoring system <NUM> typically includes a variety of computer system readable media. Such media may be any available media that is accessible by network monitoring system <NUM>, and it includes both volatile and non-volatile media, removable and non-removable media.

System memory <NUM> can include computer system readable media in the form of volatile memory, such as random access memory (RAM) <NUM> and/or cache memory <NUM>. Network monitoring system <NUM> may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, storage system <NUM> can be provided for reading from and writing to a non-removable, non-volatile magnetic media (not shown and typically called a "hard drive"). Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable, non-volatile optical disk such as a CD-ROM, DVD-ROM or other optical media can be provided. In such instances, each can be connected to bus <NUM> by one or more data media interfaces. As will be further depicted and described below, memory <NUM> may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.

Program/utility <NUM>, having a set (at least one) of program modules <NUM> (such as monitoring probe <NUM>, monitoring engine <NUM>, rule engine <NUM> and root cause analyzer <NUM>) may be stored in memory <NUM> by way of example, and not limitation, as well as an operating system, one or more application programs, other program modules, and program data. Each of the operating system, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment. Program modules generally carry out the functions and/or methodologies of embodiments of the invention as described herein.

Network monitoring system <NUM> may also communicate with one or more external devices such as a keyboard, a pointing device, a display, etc.; one or more devices that enable a user to interact with network monitoring system <NUM>; and/or any devices (e.g., network card, modem, etc.) that enable network monitoring system <NUM> to communicate with one or more other computing devices. Such communication can occur via Input/Output (I/O) interfaces <NUM>. Still yet, network monitoring system <NUM> can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and/or a public network (e.g., the Internet) via network adapter <NUM>. As depicted, network adapter <NUM> communicates with the other components of network monitoring system <NUM> via bus <NUM>. It should be understood that although not shown, other hardware and/or software components could be used in conjunction with network monitoring system <NUM>. Examples, include, but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc..

Claim 1:
A network monitoring system (<NUM>), the system (<NUM>) comprising:
a monitoring probe (<NUM>) coupled to a wireless network configured to capture packet sessions from the wireless network;
a packet analyzer coupled to the monitoring probe for analyzing a packet session captured from the wireless network by the monitoring probe, the monitoring probe including:
a processor (<NUM>);
a memory (<NUM>) coupled to the processor (<NUM>);
a database (<NUM>) including session data of a plurality of transactions in a wireless communication system (<NUM>);
a rule engine (<NUM>) configured and operable to store in the memory rules associated with a plurality of rule sets; and
an analysis engine (<NUM>) configured and operable to determine bandwidth available to packet service sessions and identify real-time bandwidth changes associated with the packet service sessions;
the analysis engine (<NUM>) configured and operable to identify, using the processor:
<NUM>) a rule set from the plurality of rule sets based upon a combination of at least two attributes of the packet service sessions selected from the following attributes: physical interface, network protocol, content source and destination identifiers, Access Point Name, interface type, and Quality of Service parameter, the rule set correlating at least two of the plurality of transactions with a cause code for a given protocol in the wireless communication system using a timestamp identifying a relative time when a failure occurs, wherein each rule in each rule set specifies the timestamp associated with occurrence of the at least two transactions correlated with one or more cause codes for each protocol, wherein different rule sets apply to different types of traffic, wherein each rule may in turn dictate a portion of that traffic that will be used in subsequent processing, and wherein the analysis engine is further configured to use the timestamp to determine which session data to read from database (<NUM>); and
<NUM>) a root cause of the failure for the at least two transactions based on at least one in the at least one identified rule set and the determined bandwidth available to packet service sessions and identified real-time bandwidth changes associated with the packet service sessions.