Diagnostic traffic generation for automatic testing and troubleshooting

A framework in a cloud network that may allow for debugging at multiple vantage points at different layers (e.g., layer 2, layer 3, etc.). The methods may provide tracer or measurement services that filter, capture, or forward flows that may include packets, calls, or protocols to look for particular signatures.

TECHNICAL FIELD

The technical field generally relates to software-defined networks and, more specifically, to testing in software-defined networks.

BACKGROUND

Communication networks have migrated from using specialized networking equipment executing on dedicated hardware, like routers, firewalls, and gateways, to virtualized network components, such as virtual network functions (VNF) and virtual machines (VM) that may be implemented or run on general purpose hardware within a cloud infrastructure. Network management of network components—whether or not virtualized—may require implementing, from time to time, software changes across the network or across a subset of the network components. These software changes may include software patches, software updates, configuration changes, or installation/uninstallation of software. In the complex computing environment today there are challenges with troubleshooting network issues that may be based on these software changes.

SUMMARY

Disclosed herein is a framework for diagnostic traffic generation for automatic testing and troubleshooting. Software-defined tracing and measurement (SD™), as disclosed herein, may allow for debugging at multiple vantage points at different layers (e.g., layer 2, layer 3, etc.). Advanced measurements apps may emulate or talk to virtual network functions to generate calls or packets or provide backend service for interactive exploration or analysis of collected data.

In an example, an apparatus may include a processor and a memory coupled with the processor that effectuates operations. The operations may include detecting an event associated with communication between a first device (e.g., a mobile device) and a second device (e.g., cloud sever) during a first period. Based on detecting the event, providing instructions to record operations by the first device or second device for a second period; and based on the recorded operations, providing instructions to install a virtual machine for generating test traffic that simulates the recorded traffic of the second period on the first device.

DETAILED DESCRIPTION

With the development of software defined networks (SDNs), there are an increasing number indirections, service chaining, application programming interfaces (APIs), and layering which may create more need to independently verify connectivity, service path, or performance. Disclosed herein is a framework for debugging of operational use cases in that may be in a SDN. Software-defined tracing and measurement (SD™), as disclosed herein, may allow for debugging at multiple vantage points at different layers (e.g., layer 2, layer 3, etc.), such as shown inFIG. 1. SD™ (e.g., diagnostic traffic generation for automatic testing and troubleshooting) may allow for tracing and measuring that may be run as a virtual network function (VNF) with flexibility and scale. SD™ service may provide tracer services that filter, capture, or forward flows that may include packets (e.g., requests or responses), commands, calls, or protocols to look for particular signatures. Tracers94may be invoked on-demand to generate test traffic. SD™ service may provide measurement services that may include deploying or controlling tracers (and collecting results), deducing expected topologies or connectivity to verify independently or interface with standard stats from other systems and network devices. Advanced measurements apps91(e.g.,FIG. 1) may 1) may emulate or talk to virtual network functions to generate calls or packets; 2) provide backend service for interactive exploration or analysis of collected data; or 3) automate measurement or tracing operations.

FIG. 2illustrates an exemplary system100that may implement VNF diagnostic traffic generation for automatic testing and troubleshooting. In system100, there may be a communications network112that may connect several devices. Exemplary devices may include switch104, switch107, router110, base station103, mobile device101, desktop computer104, or server114. Each device may include a hypervisor or the like that may be used to generate a virtual machine (VM) and corresponding virtual network functions (VNF). For example, there may be VM113in mobile device101, VM102in base station103, VM104in switch105, VM106in switch107, VM110in router111, and VM108in desktop computer109. As provided in more detail herein, VMs may be dynamically generated or removed, as needed.

FIG. 3illustrates an exemplary method for implementing software-defined tracing and measurements (SD™) as disclosed herein. At step131, server114may detect an event that triggers SD™ service. Events that may trigger SD™ services for step131may be based on types of packets traversing a network (e.g., network112), types of errors, reaching a threshold error rate, reaching a threshold traffic load, reaching a threshold packet loss, number of times an application resets or crashes, an operating system change (e.g., version), a network device change (e.g., hardware or software version), indication of a type of customer complaint, reaching a threshold number of customer complaints, date, time, location of a device (e.g., mobile device101), a billing issue, or a request from an administrator (e.g., user), among other things.

At step132, based on the event of step131, server114may determine one or more devices of interest, which may be further based on network paths of interest (e.g., one or more communication paths for uploading or downloading data). For example, inFIG. 2, cloud server105, mobile device101, or desktop computer109may be identified as devices of interest based on detecting threshold number of errors. At step133, server114may provide instructions for a VM or VNF to be activated on the one or more devices of interest. Activating the VM in step133may include providing instructions to generate a VM (or VNF) that was not already instantiated on the one more devices of interest or providing instructions to configure a VM already on the one or more devices to process or generate traffic for testing based on the situation. In an example, VM102may be configured to generate a particular type of traffic or process data as if it were a particular type of device (e.g., a mobile device or gaming server) running a particular type of application (e.g., online gaming application). In another example, VM113may generate data or functions that emulate processes that occurred when communicating with or through VM102. In this example, VM102may be an instantiated test process that simulates the functions of another VM or be the normal VM102not instantiated for testing purposes.

With continued reference toFIG. 3, at step134, server114may provide instructions for VM113on mobile device101and other VMs of interest to generate or otherwise process test traffic using the SD™ service for a test period. At step135, server114may obtain statistical information associated with the test period of step134. The statistical information may include network performance statistics, accounting data for the purpose of billing, usage data of the network or devices in the network. At step136, server114, based on the statistics of step135, may determine that one or more devices, network paths, or software applications, for example, are the source of a problem.

FIG. 4illustrates an exemplary method flow for a scenario implementing VNF diagnostic traffic generation for automatic testing and troubleshooting disclosed herein. At step141there may be general communication between mobile device101and cloud server105. Exemplary communications may be associated with e-mail, gaming, or cloud networking services, among other things. At step142, server141may detect an event. In an example, server114may periodically check statistical information associated with the general communication for mobile device101and cloud server105may send a message to server114upon detecting the event. This event may be any event, such as the events disclosed herein with reference toFIG. 3. At step143, based on the event, server114may monitor or record the network traffic (or “operations” which is a term that may generally be substituted for “traffic” as disclosed herein) of mobile device101, cloud server105, or other devices along the communication path or tangentially effect the communication between mobile device101and cloud server105, such as base station103or router110. The recorded operations may include commands or messages sent or otherwise executed by mobile device101or cloud server105. The operations or traffic may include packets (e.g., requests or responses), commands, calls, or protocols. At step144, based on the event of step142or the monitored (or recorded) traffic of step143, server114may determine devices of interest to generate test traffic. The test traffic may specifically mimic the commands recorded in step143or may generally simulate traffic associated with applications of the type of mobile device101or cloud server105. The general simulation, for example, may be a random selection of operations based on the average (or median or mode, etc.) location or other event of mobile device, cloud server, or other device of interest. Here, for example, it is determined that mobile device101and cloud server105are the devices of interest (e.g., devices that generate traffic for the SD™ service). It is contemplated herein that other devices may be selected, such as the other devices of system100. The devices of interest may be determined based on multiple factors. Factors include the events of step142or step143, or otherwise disclosed herein. Another exemplary factor may include a determination of the location, such as farthest device closest to the originator of traffic that has the device capabilities (e.g., processor speed, memory amount, bandwidth of network connection, power to the device, etc.) of creating a VM for test traffic or generating test traffic. Another example, with regard to location, may be associated with the base station in which mobile device is connected or not connected with. Another factor may be based on the intersection of complaints (or detected errors) associated with a plurality of users. For example, base station103may be selected over mobile device101based on an intersection of complaints (e.g., the device that is commonly involved in different situations) or device capability.

With continued reference toFIG. 4, at step145and step146, server114may send a message to cloud server105or may send a message to mobile device101to create VM104of cloud server105or VM113of mobile device101for generating or processing test traffic. Scenarios are contemplated herein in which VM113may be created particularly for generating test traffic for the SD™ service, while cloud server105does not create another VM (e.g., uses a previously instantiated VM used for testing) or cloud server105processes messages from VM113as it would for any other device (e.g., a VM of cloud server105already serving real traffic and is not generally aware that it is test traffic). At this step145or step146, server115may also provide instructions for the created VMS to mark the test traffic in order to recognize it at a later point in time (e.g., diagnosis at step148). In addition, server114may provide instructions to create VM or generate test traffic during a particular period. The particular period may be a period of relatively low network traffic or device usage, in order to minimize impact to a user. Or the particular period may be period of relatively high traffic or device usage, in order to more effectively diagnose problems that occur during those periods of relatively high traffic or device usage.

At step147, tests (e.g., generation of traffic and monitoring results) may occur between mobile device101and cloud server105for a period that may have been communicated at step145or step146. It is contemplated herein per-hop one-way active or passive performance measurements on each hop using the same ports and protocols as in ordinary traffic (e.g., simulate traffic that is processed as normal, but measured more discretely). At step148, server114may determine possible issues that may have caused a previous problem (e.g., problem experienced and reported by a user associated with mobile device101), may determine possible issues that may cause a problem for mobile device101(or cloud server105) in the future (e.g., after installation of a software update), or other indicators associated with health of the entire or subset of system100. Subsequently server114may provide instructions to display the determined results or transmit the results of the diagnosis of step148to a device.

FIG. 5illustrates another exemplary method for implementation of SD™. At step151, Openstack (or the like) may be used to instantiate virtual infrastructure (e.g., VMs) and inject or capture test traffic. For example, VMs and VNFs may be placed within mobile device101, base station103, router111, and desktop computer109for testing. This step151may be proactive testing of system100and may not be in response to a detected error. This method (or methods herein) may be a periodic (e.g., may occur at peak times or alternatively non-peak times). At step152, a library may be created for other VNFs to incorporate test traffic generation on command. For example, libraries to implement SD™ may be created in existing or new VNFs. At step153, vRouter (or the like) may separate test traffic (e.g., injected traffic) from real traffic (e.g., normal traffic from users). At step154, using instantiated VMs of step152in the context of SD™ to determine possible problems and suggest solutions (e.g., a configuration window may pop-up with a highlighted possible configuration at issue) or provide an indication that there are no detected problems. In other words, at step154, the health of system100may be determined and communicated.

It is contemplated herein that one or more steps of SD™ (e.g.,FIG. 3,FIG. 4, orFIG. 5) may occur on one device or may be distributed across multiple devices. Exemplary devices that may execute the disclosed methods may include an operation, administration and maintenance (OAM) server, SDN controller, router, or switch, among other things. In an exemplary implementation, distributed processing and data structures or algorithms may be used to reduce the collection traffic.

FIG. 6is a block diagram of network device300that may be connected to or comprise a component of system100. Network device300may comprise hardware or a combination of hardware and software. The functionality to facilitate telecommunications via a telecommunications network may reside in one or combination of network devices300. Network device300depicted inFIG. 6may represent or perform functionality of an appropriate network device300, or combination of network devices300, such as, for example, a component or various components of a cellular broadcast system wireless network, a processor, a server, a gateway, a node, a mobile switching center (MSC), a short message service center (SMSC), an automatic location function server (ALFS), a gateway mobile location center (GMLC), a radio access network (RAN), a serving mobile location center (SMLC), or the like, or any appropriate combination thereof. It is emphasized that the block diagram depicted inFIG. 6is exemplary and not intended to imply a limitation to a specific implementation or configuration. Thus, network device300may be implemented in a single device or multiple devices (e.g., single server or multiple servers, single gateway or multiple gateways, single controller or multiple controllers). Multiple network entities may be distributed or centrally located. Multiple network entities may communicate wirelessly, via hard wire, or any appropriate combination thereof.

Network device300may comprise a processor302and a memory304coupled to processor302. Memory304may contain executable instructions that, when executed by processor302, cause processor302to effectuate operations associated with mapping wireless signal strength. As evident from the description herein, network device300is not to be construed as software per se.

In addition to processor302and memory304, network device300may include an input/output system306. Processor302, memory304, and input/output system306may be coupled together (coupling not shown inFIG. 6) to allow communications between them. Each portion of network device300may comprise circuitry for performing functions associated with each respective portion. Thus, each portion may comprise hardware, or a combination of hardware and software. Accordingly, each portion of network device300is not to be construed as software per se. Input/output system306may be capable of receiving or providing information from or to a communications device or other network entities configured for telecommunications. For example input/output system306may include a wireless communications (e.g., 3G/4G/GPS) card. Input/output system306may be capable of receiving or sending video information, audio information, control information, image information, data, or any combination thereof. Input/output system306may be capable of transferring information with network device300. In various configurations, input/output system306may receive or provide information via any appropriate means, such as, for example, optical means (e.g., infrared), electromagnetic means (e.g., RF, Wi-Fi, Bluetooth®, ZigBee®), acoustic means (e.g., speaker, microphone, ultrasonic receiver, ultrasonic transmitter), or a combination thereof. In an example configuration, input/output system306may comprise a Wi-Fi finder, a two-way GPS chipset or equivalent, or the like, or a combination thereof.

Input/output system306of network device300also may contain a communication connection308that allows network device300to communicate with other devices, network entities, or the like. Communication connection308may comprise communication media. Communication media typically embody computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. By way of example, and not limitation, communication media may include wired media such as a wired network or direct-wired connection, or wireless media such as acoustic, RF, infrared, or other wireless media. The term computer-readable media as used herein includes both storage media and communication media. Input/output system306also may include an input device310such as keyboard, mouse, pen, voice input device, or touch input device. Input/output system306may also include an output device312, such as a display, speakers, or a printer.

Processor302may be capable of performing functions associated with telecommunications, such as functions for processing broadcast messages, as described herein. For example, processor302may be capable of, in conjunction with any other portion of network device300, determining a type of broadcast message and acting according to the broadcast message type or content, as described herein.

Memory304of network device300may comprise a storage medium having a concrete, tangible, physical structure. As is known, a signal does not have a concrete, tangible, physical structure. Memory304, as well as any computer-readable storage medium described herein, is not to be construed as a signal. Memory304, as well as any computer-readable storage medium described herein, is not to be construed as a transient signal. Memory304, as well as any computer-readable storage medium described herein, is not to be construed as a propagating signal. Memory304, as well as any computer-readable storage medium described herein, is to be construed as an article of manufacture.

Memory304may store any information utilized in conjunction with telecommunications. Depending upon the exact configuration or type of processor, memory304may include a volatile storage314(such as some types of RAM), a nonvolatile storage316(such as ROM, flash memory), or a combination thereof. Memory304may include additional storage (e.g., a removable storage318or a non-removable storage320) including, for example, tape, flash memory, smart cards, CD-ROM, DVD, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, USB-compatible memory, or any other medium that can be used to store information and that can be accessed by network device300. Memory304may comprise executable instructions that, when executed by processor302, cause processor302to effectuate operations to map signal strengths in an area of interest.

FIG. 7depicts an exemplary diagrammatic representation of a machine in the form of a computer system500within which a set of instructions, when executed, may cause the machine to perform any one or more of the methods described above. One or more instances of the machine can operate, for example, as processor302, mobile device101, server114, cloud server105, switch107, and other devices ofFIG. 2. In some embodiments, the machine may be connected (e.g., using a network100) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client user machine in a server-client user network environment, or as a peer machine in a peer-to-peer (or distributed) network environment.

Computer system500may include a processor (or controller)504(e.g., a central processing unit (CPU)), a graphics processing unit (GPU, or both), a main memory506and a static memory508, which communicate with each other via a bus510. The computer system500may further include a display unit512(e.g., a liquid crystal display (LCD), a flat panel, or a solid state display). Computer system500may include an input device514(e.g., a keyboard), a cursor control device516(e.g., a mouse), a disk drive unit518, a signal generation device520(e.g., a speaker or remote control) and a network interface device522. In distributed environments, the embodiments described in the subject disclosure can be adapted to utilize multiple display units512controlled by two or more computer systems500. In this configuration, presentations described by the subject disclosure may in part be shown in a first of display units512, while the remaining portion is presented in a second of display units512.

The disk drive unit518may include a tangible computer-readable storage medium524on which is stored one or more sets of instructions (e.g., software526) embodying any one or more of the methods or functions described herein, including those methods illustrated above. Instructions526may also reside, completely or at least partially, within main memory506, static memory508, or within processor504during execution thereof by the computer system500. Main memory506and processor504also may constitute tangible computer-readable storage media.

FIG. 8Ais a representation of an exemplary network600. Network600(e.g., system100) may comprise an SDN—that is, network600may include one or more virtualized functions implemented on general purpose hardware, such as in lieu of having dedicated hardware for every network function. That is, general purpose hardware of network600may be configured to run virtual network elements to support communication services, such as mobility services, including consumer services and enterprise services. These services may be provided or measured in sessions.

A virtual network functions (VNFs)602may be able to support a limited number of sessions. Each VNF602may have a VNF type that indicates its functionality or role. For example,FIG. 8Aillustrates a gateway VNF602aand a policy and charging rules function (PCRF) VNF602b. Additionally or alternatively, VNFs602may include other types of VNFs. Each VNF602may use one or more virtual machines (VMs)604to operate. Each VM604may have a VM type that indicates its functionality or role. For example,FIG. 8Aillustrates a management control module (MCM) VM604a, an advanced services module (ASM) VM604b, and a DEP VM604c. Additionally or alternatively, VMs604may include other types of VMs. Each VM604may consume various network resources from a hardware platform606, such as a resource608, a virtual central processing unit (vCPU)608a, memory608b, or a network interface card (NIC)608c. Additionally or alternatively, hardware platform606may include other types of resources608.

WhileFIG. 8Aillustrates resources608as collectively contained in hardware platform606, the configuration of hardware platform606may isolate, for example, certain memory608cfrom other memory608c.FIG. 8Bprovides an exemplary implementation of hardware platform606.

Hardware platform606may comprise one or more chasses610. Chassis610may refer to the physical housing or platform for multiple servers or other network equipment. In an aspect, chassis610may also refer to the underlying network equipment. Chassis610may include one or more servers612. Server612may comprise general purpose computer hardware or a computer. In an aspect, chassis610may comprise a metal rack, and servers612of chassis610may comprise blade servers that are physically mounted in or on chassis610.

Each server612may include one or more network resources608, as illustrated. Servers612may be communicatively coupled together (not shown) in any combination or arrangement. For example, all servers612within a given chassis610may be communicatively coupled. As another example, servers612in different chasses610may be communicatively coupled. Additionally or alternatively, chasses610may be communicatively coupled together (not shown) in any combination or arrangement.

The characteristics of each chassis610and each server612may differ. For example,FIG. 8Billustrates that the number of servers612within two chasses610may vary. Additionally or alternatively, the type or number of resources610within each server612may vary. In an aspect, chassis610may be used to group servers612with the same resource characteristics. In another aspect, servers612within the same chassis610may have different resource characteristics.

Given hardware platform606, the number of sessions that may be instantiated may vary depending upon how efficiently resources608are assigned to different VMs604. For example, assignment of VMs604to particular resources608may be constrained by one or more rules. For example, a first rule may require that resources608assigned to a particular VM604be on the same server612or set of servers612. For example, if VM604uses eight vCPUs608a, 1 GB of memory608b, and 2 NICs608c, the rules may require that all of these resources608be sourced from the same server612. Additionally or alternatively, VM604may require splitting resources608among multiple servers612, but such splitting may need to conform with certain restrictions. For example, resources608for VM604may be able to be split between two servers612. Default rules may apply. For example, a default rule may require that all resources608for a given VM604must come from the same server612.

An affinity rule may restrict assignment of resources608for a particular VM604(or a particular type of VM604). For example, an affinity rule may require that certain VMs604be instantiated on (that is, consume resources from) the same server612or chassis610. For example, if VNF602uses six MCM VMs604a, an affinity rule may dictate that those six MCM VMs604abe instantiated on the same server612(or chassis610). As another example, if VNF602uses MCM VMs604a, ASM VMs604b, and a third type of VMs604, an affinity rule may dictate that at least the MCM VMs604aand the ASM VMs604bbe instantiated on the same server612(or chassis610). Affinity rules may restrict assignment of resources608based on the identity or type of resource608, VNF602, VM604, chassis610, server612, or any combination thereof.

An anti-affinity rule may restrict assignment of resources608for a particular VM604(or a particular type of VM604). In contrast to an affinity rule—which may require that certain VMs604be instantiated on the same server612or chassis610—an anti-affinity rule requires that certain VMs604be instantiated on different servers612(or different chasses610). For example, an anti-affinity rule may require that MCM VM604abe instantiated on a particular server612that does not contain any ASM VMs604b. As another example, an anti-affinity rule may require that MCM VMs604afor a first VNF602be instantiated on a different server612(or chassis610) than MCM VMs604afor a second VNF602. Anti-affinity rules may restrict assignment of resources608based on the identity or type of resource608, VNF602, VM604, chassis610, server612, or any combination thereof.

Within these constraints, resources608of hardware platform606may be assigned to be used to instantiate VMs604, which in turn may be used to instantiate VNFs602, which in turn may be used to establish sessions. The different combinations for how such resources608may be assigned may vary in complexity and efficiency. For example, different assignments may have different limits of the number of sessions that can be established given a particular hardware platform606.

For example, consider a session that may require gateway VNF602aand PCRF VNF602b. Gateway VNF602amay require five VMs604instantiated on the same server612, and PCRF VNF602bmay require two VMs604instantiated on the same server612. (Assume, for this example, that no affinity or anti-affinity rules restrict whether VMs604for PCRF VNF602bmay or must be instantiated on the same or different server612than VMs604for gateway VNF602a.) In this example, each of two servers612may have sufficient resources608to support 10 VMs604. To implement sessions using these two servers612, first server612may be instantiated with 10 VMs604to support two instantiations of gateway VNF602a, and second server612may be instantiated with 9 VMs: five VMs604to support one instantiation of gateway VNF602aand four VMs604to support two instantiations of PCRF VNF602b. This may leave the remaining resources608that could have supported the tenth VM604on second server612unused (and unusable for an instantiation of either a gateway VNF602aor a PCRF VNF602b). Alternatively, first server612may be instantiated with 10 VMs604for two instantiations of gateway VNF602aand second server612may be instantiated with 10 VMs604for five instantiations of PCRF VNF602b, using all available resources608to maximize the number of VMs604instantiated.

Consider, further, how many sessions each gateway VNF602aand each PCRF VNF602bmay support. This may factor into which assignment of resources608is more efficient. For example, consider if each gateway VNF602asupports two million sessions, and if each PCRF VNF602bsupports three million sessions. For the first configuration—three total gateway VNFs602a(which satisfy the gateway requirement for six million sessions) and two total PCRF VNFs602b(which satisfy the PCRF requirement for six million sessions)—would support a total of six million sessions. For the second configuration—two total gateway VNFs602a(which satisfy the gateway requirement for four million sessions) and five total PCRF VNFs602b(which satisfy the PCRF requirement for 15 million sessions)—would support a total of four million sessions. Thus, while the first configuration may seem less efficient looking only at the number of available resources608used (as resources608for the tenth possible VM604are unused), the second configuration is actually more efficient from the perspective of being the configuration that can support more the greater number of sessions.

To solve the problem of determining a capacity (or, number of sessions) that can be supported by a given hardware platform605, a given requirement for VNFs602to support a session, a capacity for the number of sessions each VNF602(e.g., of a certain type) can support, a given requirement for VMs604for each VNF602(e.g., of a certain type), a give requirement for resources608to support each VM604(e.g., of a certain type), rules dictating the assignment of resources608to one or more VMs604(e.g., affinity and anti-affinity rules), the chasses610and servers612of hardware platform606, and the individual resources608of each chassis610or server612(e.g., of a certain type), an integer programming problem may be formulated.

As described herein, a telecommunications system wherein management and control utilizing a software designed network (SDN) and a simple IP are based, at least in part, on user equipment, may provide a wireless management and control framework that enables common wireless management and control, such as mobility management, radio resource management, QoS, load balancing, etc., across many wireless technologies, e.g. LTE, Wi-Fi, and future 5G access technologies; decoupling the mobility control from data planes to let them evolve and scale independently; reducing network state maintained in the network based on user equipment types to reduce network cost and allow massive scale; shortening cycle time and improving network upgradability; flexibility in creating end-to-end services based on types of user equipment and applications, thus improve customer experience; or improving user equipment power efficiency and battery life—especially for simple M2M devices—through enhanced wireless management.

While examples of a telecommunications system in which diagnostic traffic generation for automatic testing and troubleshooting may be processed and managed have been described in connection with various computing devices/processors, the underlying concepts may be applied to any computing device, processor, or system capable of facilitating a telecommunications system. The various techniques described herein may be implemented in connection with hardware or software or, where appropriate, with a combination of both. Thus, the methods and devices may take the form of program code (i.e., instructions) embodied in concrete, tangible, storage media having a concrete, tangible, physical structure. Examples of tangible storage media include floppy diskettes, CD-ROMs, DVDs, hard drives, or any other tangible machine-readable storage medium (computer-readable storage medium). Thus, a computer-readable storage medium is not a signal. A computer-readable storage medium is not a transient signal. Further, a computer-readable storage medium is not a propagating signal. A computer-readable storage medium as described herein is an article of manufacture. When the program code is loaded into and executed by a machine, such as a computer, the machine becomes a device for telecommunications. In the case of program code execution on programmable computers, the computing device will generally include a processor, a storage medium readable by the processor (including volatile or nonvolatile memory or storage elements), at least one input device, and at least one output device. The program(s) can be implemented in assembly or machine language, if desired. The language can be a compiled or interpreted language, and may be combined with hardware implementations.

The methods and devices associated with a telecommunications system as described herein also may be practiced via communications embodied in the form of program code that is transmitted over some transmission medium, such as over electrical wiring or cabling, through fiber optics, or via any other form of transmission, wherein, when the program code is received and loaded into and executed by a machine, such as an EPROM, a gate array, a programmable logic device (PLD), a client computer, or the like, the machine becomes a device for implementing telecommunications as described herein. When implemented on a general-purpose processor, the program code combines with the processor to provide a unique device that operates to invoke the functionality of a telecommunications system.

While a telecommunications system has been described in connection with the various examples of the various figures, it is to be understood that other similar implementations may be used or modifications and additions may be made to the described examples of a telecommunications system without deviating therefrom. For example, one skilled in the art will recognize that a telecommunications system as described in the instant application may apply to any environment, whether wired or wireless, and may be applied to any number of such devices connected via a communications network and interacting across the network. Therefore, a telecommunications system as described herein should not be limited to any single example, but rather should be construed in breadth and scope in accordance with the appended claims.

In describing preferred methods, systems, or apparatuses of the subject matter of the present disclosure—diagnostic traffic generation for automatic testing and troubleshooting—as illustrated in the Figures, specific terminology is employed for the sake of clarity. The claimed subject matter, however, is not intended to be limited to the specific terminology so selected, and it is to be understood that each specific element includes all technical equivalents that operate in a similar manner to accomplish a similar purpose. In addition, the use of the word “or” is generally used inclusively unless otherwise provided herein. It is contemplated that steps ofFIG. 3,FIG. 4, orFIG. 5, for example, may be skipped or combined.