This application claims the priority benefit of Romanian Patent Application Serial No. a 2019 00814, filed Nov. 28, 2019, the disclosure of which is incorporated herein by reference in its entirety.
The subject matter described herein relates to network equipment testing. More particularly, the subject matter described herein relates to methods, systems, and computer readable media for implementing a generalized model for defining application state machines.
While state machines have been utilized for the purpose conducting network traffic testing at a device under test, the use of these state machines has generally been confined to specific communication protocols that are directly incorporated into the application state machines. More specifically, the entirety of a specific communication protocol to be used for testing is typically embedded into a test engine in an attempt to minimize the consumption of resources. However, a test system that is tasked to simulate diverse network behaviors corresponding to a large number of emulated users is notably restricted when such testing is limited to the communications protocols integrated into the test engine. Namely, accurate testing necessitates a test system that can produce realistic and complex mixes of network traffic that is not constrained to a specific protocol. Other challenges associated with test systems restricted in this manner include extensive resource requirement costs as well as the significant time requirements that are associated with the provisioning and supporting of new testing scenarios.
Accordingly, there exists a need for methods, systems, and computer readable media for implementing a generalized model for defining application state machines.
According to one aspect, the subject matter described herein includes a method for implementing a generalized model for defining application state machines that includes utilizing a user behavioral state machine construct layer of a generalized application emulation model (GAEM) system to emulate a plurality of high level user behaviors originating from a plurality of emulated network users and utilizing a business application logic state machine construct layer in the GAEM system to emulate access rules and policies of an application to be defined. The method further includes utilizing a message parsing state machine construct layer in the GAEM system to emulate input/output (IO) events and network messaging events originating from emulated network entities and utilizing at least one network traffic processing agent in the GAEM system that is configured to establish an execution environment for facilitating the interactions among the user behavioral state machine construct layer, business application logic state machine construct layer, and the message parsing state machine construct layer such that when executed in the execution environment, the interactions establish a definition for a state machine that is representative of the application.
In one example of the method, the high level user behaviors are represented as parallel tracks, wherein each of the parallel tracks is a sequence of operations that is exposed by one or more applications.
In one example of the method, two or more of the parallel tracks are synchronized together at synchronization points.
In one example of the method, an output of one or more of the construct layers is provided to the at least one network traffic processing agent for execution.
In one example of the method, emulated network packet traffic is generated by the at least one network traffic processing agent.
In one example of the method, the user behavioral state machine construct layer, the business application logic state machine construct layer, and the message parsing state machine construct layer are configured to communicate data via filing of events.
In one example of the method, service access rules associated with the business application logic state machine construct layer are defined by an operator of a network under test.
According to one aspect, the subject matter described herein includes a system for implementing a generalized model for defining application state machines that comprises a user behavioral state machine construct layer configured to emulate a plurality of high level user behaviors originating from a plurality of emulated network users and a business application logic state machine construct layer configured to emulate access rules and policies of an application to be defined. The system further includes a message parsing state machine construct layer configured to emulate input/output (IO) events and network messaging events originating from emulated network entities and at least one network traffic processing agent that is configured to establish an execution environment for facilitating the interactions among the user behavioral state machine construct layer, the business application logic state machine construct layer, and the message parsing state machine construct layer such that when executed in the execution environment, the interactions establish a definition for a state machine that is representative of the application.
In one example of the system, the high level user behaviors are represented as parallel tracks, wherein each of the parallel tracks is a sequence of operations that is exposed by one or more applications.
In one example of the system, two or more of the parallel tracks are synchronized together at synchronization points.
In one example of the system, an output of one or more of the construct layers is provided to the at least one network traffic processing agent for execution.
In one example of the system, emulated network packet traffic is generated by the at least one network traffic processing agent.
In one example of the system, the user behavioral state machine construct layer, the business application logic state machine construct layer, and the message parsing state machine construct layer are configured to communicate data via filing of events.
In one example of the system, service access rules associated with the business application logic state machine construct layer are defined by an operator of a network under test.
The subject matter described herein can be implemented in software in combination with hardware and/or firmware. For example, the subject matter described herein can be implemented in software executed by a processor. In one exemplary implementation, the subject matter described herein can be implemented using a non-transitory computer readable medium having stored thereon computer executable instructions that when executed by a processor of a computer control the computer to perform steps. Exemplary computer readable media suitable for implementing the subject matter described herein include non-transitory computer-readable media, such as disk memory devices, chip memory devices, programmable logic devices, and application specific integrated circuits. In addition, a computer readable medium that implements the subject matter described herein may be located on a single device or computing platform or may be distributed across multiple devices or computing platforms.
Preferred embodiments of the subject matter described herein will now be explained with reference to the accompanying drawings, wherein like reference numerals represent like parts, of which:
In accordance with the subject matter disclosed herein, methods, systems, and computer readable media for generalized model for defining application state machines are provided. In some embodiments, the subject matter described herein relates to a network test system that generates highly realistic network user traffic associated with various protocols at large scale (e.g., a large number of simultaneous user emulations) for the purposes of testing a device under test (DUT) or system under test (SUT). In some embodiments, the disclosed subject matter may pertain to applications beyond network testing, such as network monitoring, network security, facilitating smart contracts, and the like.
In some embodiments, the disclosed subject matter may be implemented as an application security testing system 102. As shown in
As shown in
In some embodiments, SM model synthesizer 106 can be configured to synthesize the state machine definitions of the state machine traffic model using a high-level programming language (e.g., Python). Further, the state machine definitions can be synthesized using a high-level programming such that the state machine models can be segmented into state machine fragments. These state machine fragments can be programmed or logically interconnected by SM model synthesizer 106 to provide a desired testing functionality. Further, the state machine fragments can be stored by SM model synthesizer 106 in a local SM library 108 for subsequent access and use. More specifically, state machine definitions can be synthesized by synthesizer 106 using a reusable and extensible library of state machine fragments (SMFs) maintained in SM library 108. Further, the SMFs may be written in Python or other suitable programming language. Different test operator objectives and/or goals may require the synthesis of various SM-based traffic definitions, which are constructed and dynamically implemented into a generalized application emulation model (GAEM) engine (e.g., GAEM engine 118 or 120).
In some embodiments, a GAEM engine is responsible for establishing and defining a plurality of state machines corresponding to the state machine definitions received from controller 110. Notably, a GAEM engine can be a generic and/or protocol agnostic engine that can be implemented in software and run on a wide variety of test system-related hardware nodes. For example, the hosting hardware node can include an adjunct server, an appliance device, an internal processor, or the like. Other nodes can comprise an hardware component with an installed operating system. Alternatively, a node as used herein can be a virtual machine, cloud computing instance, or the like. In some embodiments, the GAEM engine is implemented in software that can be incorporated into and/or executed by an agent, such as client agent 114 or server agent 116 as shown in
Notably, the state machine definitions of a state machine traffic model may be provided by SM model synthesizer 106 to test management controller 110 for distribution to GAEM engines 118 and 120. In some embodiments, test management controller 110 is primarily responsible for managing all of the agents (and their respective host nodes) in system 102. For example, test management controller 110 can be configured to distribute the different state machine definitions (e.g., application definitions) and associated user inputs to the different agents (e.g., agents 114 and 116). Test management controller 110 can also be configured to assign different application profiles or roles to each of the agents based on the state machine definitions and associated user inputs (that the controller distributes among all the agents).
As indicated above, the application state machine definitions (along with user input data) can be delivered and provisioned in a GAEM engine, which provides a state machine execution environment. Notably, there is a GAEM engine residing in each agent of application security test system 102, e.g., client agent 114 and server agent 116. Once the state machine definitions are provisioned in the agents, each GAEM engine can use the definitions to execute the application state machines, which are configured to perform one or more test emulation functions, such as generating test network traffic. Specifically, the client and server agents are configured to generate network traffic test packets and packet flows in accordance with the definitions of the executed SM model. As shown in
In some embodiments, the GAEM engine is configured to use the synthesized SM definitions (e.g., application state machine definitions) to define and generate a respective application state machine that is executed within an agent. For example, each state machine can be defined by a set of states (), a set of events (), a set of actions (), an initial state (), and a map. For example, an exemplary state machine can be defined as follows:
→i.e.,
−
Notably, each action is defined as a sequence of well-known instructions. Each application state machine definition also includes a set of exposed operations (). In some embodiments, the operation includes a plurality of elements, where each element is a tuple comprising i) an initiating event, ii) a set of states indicating successful termination, and iii) a set of statistics indicating failed termination.
According to another aspect of the subject matter described herein, one application definition can inherit a definition from another application state machine definition. Since each application state machine definition is composed of transition tables and/or maps (represented by in the examples above), emulated applications can be extended by referring to base transition tables and defining differences existing in the base transition tables in terms of i) adding new transitions to the base tables, ii) deleting transitions from the base tables, and/or iii) modifying transitions in the base tables. Notably, the application definition may define a plurality of actors (e.g., one or more server actors and client actors) that are involved with the execution of an application.
In some embodiments, client agent 114 and server agent 116 may each include traffic generation hardware modules (e.g., transmission hardware engines) that are implemented, at least in part, in programmable logic devices such as field programmable gate arrays (FPGAs) and/or multi-core central processing units (CPUs). These traffic generation hardware modules further include networking device ports that can be used to establish a connection with the device under test 122. As shown in
Although not depicted in
Similarly, the second layer is represented in
Lastly, the on-the-wire SM construct layer is represented as a message parsing state machine construct layer 205 that is configured to model and emulate the messaging and associated messaging protocols used by an emulated network user. As shown in
Another source of events can be attributed to the input/output activity occurring in the lower layer of the application (e.g., lower layer I/O 218). In particular, input/output (I/O) events can be filed from message parsing state machine construct layer 205 to application business construct layer 204 as shown in
Furthermore, lower layer I/O 218 can also be configured to send packets to a message parsing logic state machine 220 hosted by message parsing state machine construct layer 205. In some embodiments, the packets received by message parsing logic state machine 220 are received over the wire via a network interface port. Notably, message parsing logic state machine 220 is configured to receive the packets and forward them to application business construct layer 204 for processing. In some embodiments, application business construct layer 204 is configured to determine the initial state of the application state machine, inspect the bytes or signature contained in the received packets. Depending on the protocol or data indicated by the inspected bytes/signature in the packets, application business construct layer 204 is configured to utilize the determined data and the determined initial state to access a state transition table. Notably, the state transition table will indicate if the particular event associated with the initial state and the determined data has triggered a transition in the state machine. For example, message parsing state machine construct layer 205 can utilize this process to discern between whether certain expected attachments were received or alternatively, an error occurred.
In block 702, method 700 includes utilizing a user behavioral state machine construct layer of a generalized application emulation model (GAEM) system to emulate a plurality of high level user behaviors originating from a plurality of emulated network users. In some embodiments, the high level user behaviors are represented as parallel tracks, wherein each of the parallel tracks is a sequence of operations that is exposed by one or more applications.
In block 704, method 700 includes utilizing a business application logic state machine construct layer in the GAEM system to emulate access rules (e.g., service access rules) and policies of an application to be defined.
In block 704, method 700 includes utilizing a message parsing state machine construct layer in the GAEM system to emulate input/output (IO) events and network messaging events originating from emulated network entities.
In block 706, method 700 includes utilizing at least one network traffic processing agent in the GAEM system that is configured to establish an execution environment for facilitating the interactions among the user behavioral state machine construct layer, business application logic state machine construct layer, and the message parsing state machine construct layer such that when executed in the execution environment, the interactions establish a definition for a state machine that is representative of the application.
It should be noted that each of the GAEM engine and/or functionality described herein may constitute one or more special purpose computing devices constituting a practical application. Further, embodiments of the GAEM and/or functionality described herein can improve the technological field of network traffic testing environments by implementing a new test system that produces realistic and complex mixes of network traffic associated with a large number of users. For example, the use of a GAEM engine system enables a DUT/SUT test operator to describe network user behaviors at a high level as well as to specify application business logic rules that are to be applied in the DUT/SUT. As such, large scale testing scenarios (e.g., large number of simultaneous user emulations) may be conducted in a more efficient and realistic manner while also utilizing less computing resources than other network testing implementations.
It will be understood that various details of the subject matter described herein may be changed without departing from the scope of the subject matter described herein. Furthermore, the foregoing description is for the purpose of illustration only, and not for the purpose of limitation.
Number | Name | Date | Kind |
---|---|---|---|
5247517 | Ross et al. | Sep 1993 | A |
5327437 | Balzer | Jul 1994 | A |
5343463 | van Tetering et al. | Aug 1994 | A |
5477531 | McKee | Dec 1995 | A |
5535338 | Krause et al. | Jul 1996 | A |
5568471 | Hershey et al. | Oct 1996 | A |
5590285 | Krause et al. | Dec 1996 | A |
5600632 | Schulman | Feb 1997 | A |
5657438 | Wygodny | Aug 1997 | A |
5671351 | Wild | Sep 1997 | A |
5761486 | Watanabe | Jun 1998 | A |
5787253 | McCreery et al. | Jul 1998 | A |
5838919 | Schwaller et al. | Nov 1998 | A |
5850386 | Anderson et al. | Dec 1998 | A |
5878032 | Mirek et al. | Mar 1999 | A |
5881237 | Schwaller et al. | Mar 1999 | A |
5905713 | Anderson et al. | May 1999 | A |
5937165 | Schwaller et al. | Aug 1999 | A |
5974237 | Shurmer et al. | Oct 1999 | A |
6028847 | Beanland | Feb 2000 | A |
6044091 | Kim | Mar 2000 | A |
6061725 | Schwaller et al. | May 2000 | A |
6065137 | Dunsmore et al. | May 2000 | A |
6108800 | Asawa | Aug 2000 | A |
6122670 | Bennett et al. | Sep 2000 | A |
6148277 | Asava | Nov 2000 | A |
6157955 | Narad et al. | Dec 2000 | A |
6172989 | Yanagihara et al. | Jan 2001 | B1 |
6173333 | Jolitz | Jan 2001 | B1 |
6189031 | Badger | Feb 2001 | B1 |
6233256 | Dieterich et al. | May 2001 | B1 |
6279124 | Brouwer | Aug 2001 | B1 |
6321264 | Fletcher | Nov 2001 | B1 |
6345302 | Bennett et al. | Feb 2002 | B1 |
6360332 | Weinberg | Mar 2002 | B1 |
6363056 | Beigi et al. | Mar 2002 | B1 |
6397359 | Chandra et al. | May 2002 | B1 |
6401117 | Narad | Jun 2002 | B1 |
6408335 | Schwaller et al. | Jun 2002 | B1 |
6421730 | Narad | Jul 2002 | B1 |
6434513 | Sherman et al. | Aug 2002 | B1 |
6446121 | Shah | Sep 2002 | B1 |
6507923 | Wall et al. | Jan 2003 | B1 |
6545979 | Poulin | Apr 2003 | B1 |
6601098 | Case | Jul 2003 | B1 |
6621805 | Kondylis et al. | Sep 2003 | B1 |
6625648 | Schwaller et al. | Sep 2003 | B1 |
6625689 | Narad | Sep 2003 | B2 |
6662227 | Boyd et al. | Dec 2003 | B2 |
6708224 | Tsun et al. | Mar 2004 | B1 |
6763380 | Mayton et al. | Jul 2004 | B1 |
6789100 | Nemirovsky | Sep 2004 | B2 |
6920407 | Adamian et al. | Jul 2005 | B2 |
6950405 | Van Gerrevink | Sep 2005 | B2 |
6996772 | Justice et al. | Feb 2006 | B2 |
7006963 | Maurer | Feb 2006 | B1 |
7010782 | Narayan et al. | Mar 2006 | B2 |
7516216 | Ginsberg et al. | Apr 2009 | B2 |
7543054 | Bansod et al. | Jun 2009 | B1 |
7765313 | Jain et al. | Jul 2010 | B2 |
8010469 | Kapoor et al. | Aug 2011 | B2 |
8023410 | O'Neill | Sep 2011 | B2 |
8135657 | Kapoor et al. | Mar 2012 | B2 |
8145949 | Silver | Mar 2012 | B2 |
8341462 | Broda et al. | Dec 2012 | B2 |
8402313 | Pleis et al. | Mar 2013 | B1 |
8447839 | Jiang et al. | May 2013 | B2 |
8510600 | Broda et al. | Aug 2013 | B2 |
8522089 | Jindal | Aug 2013 | B2 |
8601585 | Beddoe et al. | Dec 2013 | B2 |
8676188 | Olgaard | Mar 2014 | B2 |
8839035 | Dimitrovich et al. | Sep 2014 | B1 |
9043746 | Rabinovich et al. | May 2015 | B2 |
9065556 | Popescu et al. | Jun 2015 | B2 |
9075735 | Tomlinson et al. | Jul 2015 | B2 |
9116873 | Majumdar et al. | Aug 2015 | B2 |
9131000 | Iyer | Sep 2015 | B2 |
9178790 | Majumdar et al. | Nov 2015 | B2 |
9178823 | Majumdar et al. | Nov 2015 | B2 |
9397901 | Majumdar et al. | Jul 2016 | B2 |
9578441 | Gerber et al. | Feb 2017 | B2 |
20020080781 | Gustavsson | Jun 2002 | A1 |
20030009544 | Wach | Jan 2003 | A1 |
20030012141 | Gerrevink | Jan 2003 | A1 |
20030033406 | Rekesh et al. | Feb 2003 | A1 |
20030043434 | Brachmann et al. | Mar 2003 | A1 |
20030231741 | Rancu et al. | Dec 2003 | A1 |
20050022012 | Bluestone et al. | Jan 2005 | A1 |
20060242499 | Volz | Oct 2006 | A1 |
20060268933 | Kellerer et al. | Nov 2006 | A1 |
20080285467 | Olgaard | Nov 2008 | A1 |
20080298380 | Rittmeyer et al. | Dec 2008 | A1 |
20090100296 | Srinivasan et al. | Apr 2009 | A1 |
20090100297 | Srinivasan et al. | Apr 2009 | A1 |
20090112668 | Abu El Ata | Apr 2009 | A1 |
20100050040 | Samuels et al. | Feb 2010 | A1 |
20110238855 | Korsunsky et al. | Sep 2011 | A1 |
20110283247 | Ho et al. | Nov 2011 | A1 |
20120144226 | Yang et al. | Jun 2012 | A1 |
20120192021 | Jindal | Jul 2012 | A1 |
20120240185 | Kapoor et al. | Sep 2012 | A1 |
20120314576 | Hasegawa et al. | Dec 2012 | A1 |
20130006567 | Horn | Jan 2013 | A1 |
20130060735 | Haddy et al. | Mar 2013 | A1 |
20130111257 | Broda et al. | May 2013 | A1 |
20130208600 | Campbell et al. | Aug 2013 | A1 |
20130227092 | Maestas | Aug 2013 | A1 |
20130275606 | Iyer | Oct 2013 | A1 |
20130286860 | Dorenbosch et al. | Oct 2013 | A1 |
20130346719 | Tomlinson et al. | Dec 2013 | A1 |
20140036700 | Majumdar et al. | Feb 2014 | A1 |
20140100297 | Gruskin et al. | Apr 2014 | A1 |
20140115394 | Fattah | Apr 2014 | A1 |
20140160927 | Majumdar et al. | Jun 2014 | A1 |
20140169177 | Popescu et al. | Jun 2014 | A1 |
20140173094 | Majumdar et al. | Jun 2014 | A1 |
20140289561 | Majumdar et al. | Sep 2014 | A1 |
20160094497 | Javed | Mar 2016 | A1 |
20160218884 | Ebrom | Jul 2016 | A1 |
20170255884 | Visvanathan | Sep 2017 | A1 |
Number | Date | Country |
---|---|---|
0895375 | Aug 2004 | EP |
Entry |
---|
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 13/718,813 (dated Mar. 17, 2016). |
Final Office Action for U.S. Appl. No. 13/718,813 (dated Sep. 1, 2015). |
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 13/447,160 (dated Apr. 30, 2015). |
Applicant-Initiated Interview Summary for U.S. Appl. No. 13/447,160 (dated Mar. 26, 2015). |
Advisory Action for U.S. Appl. No. 13/447,160 (dated Mar. 5, 2015). |
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 13/716,077 (dated Feb. 20, 2015). |
Non-Final Office Action for U.S. Appl. No. 13/718,813 (dated Jan. 14, 2015). |
Final Office Action for U.S. Appl. No. 13/447,160 (dated Dec. 19, 2014). |
Non-Final Office Action for U.S. Appl. No. 13/716,077 (dated Sep. 24, 2014). |
Non-Final Office Action for U.S. Appl. No. 13/447,160 (dated Jul. 10, 2014). |
Advisory Action for U.S. Appl. No. 13/447,160 (dated May 29, 2014). |
Applicant-Initiated Interview Summary for U.S. Appl. No. 13/447,160 (dated May 23, 2014). |
Final Office Action for U.S. Appl. No. 13/447,160 (dated Mar. 18, 2014). |
Interview Summary for U.S. Appl. No. 13/447,160 (dated Feb. 25, 2014). |
Non-Final Office Action for U.S. Appl. No. 13/447,160 (dated Nov. 8, 2013). |
“3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Physical Channels and Modulation (Release 10),” 3GPP TS 36.211, V10.3.0 (Sep. 2011). |
Dutta et al., “A Tight Lower Bound for Parity in Noisy Communcations Networks,” Tata Institute of Fundamental Research, pp. 1056-1065 (2008). |
Abbes et al., “Protocol Analysis in Intrusion Detection Using Decision Tree,” IEEE, Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04), pp. 1-5 (2004). |
Nilsson et al., “The Scalable Tree Protocol—A Cache Coherence Approach for Large-Scale Multiprocessors,” IEEE, pp. 498-506 (1992). |
Sleator et al., “Self-Adjusting Binary Search Trees,” Journal of the Association for Computing Machinery. Vol. 32, No. 3, pp. 652-686 (Jul. 1985). |
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 13/712,499 (dated Jun. 22, 2015). |
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 13/567,747 (dated Jun. 22, 2015). |
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 13/871,909 (dated Apr. 20, 2015). |
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 13/712,499 (dated Mar. 11, 2015). |
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 13/567,747 (dated Mar. 5, 2015). |
Non-Final Office Action for U.S. Appl. No. 13/871,909 (dated Nov. 20, 2014). |
Non-Final Office Action for U.S. Appl. No. 13/567,747 (dated Nov. 19, 2014). |
Non-Final Office Action for U.S. Appl. No. 13/712,499 (dated Jul. 14, 2014). |
“Ixload Specifications,” http://web.archive.org/web/20130127053319// www.ixiacom.com/products/network_test/applications/ixload/specifications/index.php. pp. 1-7, (Jan. 27, 2013). |
“A TCP Tutorial,” ssfnet.org/Exchange/tcp/tcpTutorialNotes.html, pp. 1-10 (Apr. 4, 2012). |
“IxLoad,” Solution Brief, 915-3030-01. D, Ixia, pp. 1-4 (Feb. 2012). |
Notice of Allowance and Fee(s) Due for U.S. Appl. No. 11/462,351 (dated Feb. 6, 2009). |
Restriction Requirement for U.S. Appl. No. 11/462,351 (dated Jan. 2, 2009). |
Ye et al., “Large-Scale Network Parameter Configuration Using an On-line Simulation Framework,” Technical report, ECSE Department, Rensselear Polytechnic Institute (2002). |
Business Wire, “Ixia's Web Stressing and In-Service Monitoring Products Names Best of Show Finalist at NetWorld+Interop 2001, Atlanta,” 2 pages (Sep. 10, 2001). |
PRNewsWire, “Caw Network Doubles Performance of Real-World Capacity Assessment Appliance Suite: WebAvalanche and WebReflector Now Generate and Respond to 20,000+ HTTP requests per Second With Over One Million Open Connections,” 2 pages (Sep. 10, 2001). |
Caw Networks, Inc. and Foundry Networks, Inc., “Caw Networks Performance Brief: Caw Networks and Foundry Networks 140,000 Transactions per Second Assessment,” 1 page (Sep. 7, 2001). |
MacVittie, “Online Only: CAW's WebReflector Makes Load-Testing a Cakewalk,” Network Computing, 2 pages (Sep. 3, 2001). |
Business Wire, “REMINDER/Caw Networks to Spotlight WebAvalanche 2.0 and WebReflector At Networld+Interop,” 2 pages (May 8, 2001). |
“Caw Networks Unveils New Web-Stressing Appliance,” press release from Caw Networks, Inc., 2 pages (Mar. 5, 2001). |
Ye et al., “Network Management and Control Using collaborative On-Line Simulation,” Proc. IEEE International Conference on Communications ICC2001, Helsinki, Finland, pp. 1-8 (2001). |
Business Wire, “NetIQ's Chariot 4.0 Goes Internet-Scale; ASPs and Service Providers Can Conduct Tests With Up to 10,000 Connections; New Visual Test Designer Simplifies Testing of All Sizes,” 1 page (Oct. 23, 2000). |
Business Wire, “Spirient Communications TeraMetrics and NetIQ's Chariot Work Together to Create First Complete Network Performance Analysis Solution,” 2 pages (Sep. 25, 2000). |
Kovac, “Validate your equipment performance—Netcom Systems' SmartBits—Hardware Review—Evaluation,” Communications News, 2 pages (May 2000). |
Marchette, “A Statistical Method for Profiling Network Traffic,” USENIX (Apr. 12-19, 1999). |
Cooper et al., “Session traces: an enhancement to network simulator,” Performance, computing and Communications Conference, Scottsdale, AZ (Feb. 1, 1999). |
San-qi, et al., “SMAQ: A Measurement-Based Tool for Traffic Modeling and Queuing Analysis Part I; Design methodologies and software architecture,” IEEE Communications Magazine, pp. 56-65 (Aug. 1, 1998). |
San-qi, et al., “SMAQ: A Measurement-Based Tool for Traffic Modeling and Queuing Analysis Part II; Network Applications,” IEEE Communications Magazine, pp. 66-77 (Aug. 1, 1998). |
Mneimneh, “Computer Networks Flow control with TCP,” pp. 1-5 (Publication Date Unknown). |
Pinheiro et al., “FSM-Based Test Case Generation Methods Applied to Test the Communication Software on Board the ITASAT University Satellite: A Case Study,” Journal of Aerospace Technology and Management, vol. 6 No. 4, pp. 447-461 (Oct. 2014). |
“Using Finite State Machine at the Testing of Network Protocols,” ResearchGate, pp. 1-6 (Oct. 2011). |
Yang et al., “An Automated Mechanism of Security Test on Network Protocols,” 2009 Fifth International Conference on Information Assurance and Securtiy,IEEE Computer Society, pp. 503-506 (2009). |
Gineste et al., “Programmable Active Emulation of Wireless Systems—A DVB-RCS Example,” WIOPT, pp. 1-6 (Apr. 2008). |
Number | Date | Country | |
---|---|---|---|
20210165672 A1 | Jun 2021 | US |