Network transaction discovery
First Claim
1. A computer network system for identifying resources used in a network transaction, the system comprising:
- a plurality of computer systems communicatively coupled to a computer network;
wherein one or more of the plurality of computers systems comprises a programmable processor and the programmable processor is configured to execute;
a robotic transaction playback client configured to initiate re-execution of a recorded transaction;
a network record collector; and
a backend processor;
wherein the backend processor performs identification analysis by analyzing newly collected data, the newly collected data being collected by the network record collector in response to one or more transactions re-executed by the robotic transaction playback client to identify one or more resources used in the one or more transactions, the identification analysis comprising;
identifying a plurality of network paths potentially corresponding to the transaction;
assigning equal base probabilities to each of the plurality of network paths;
analyzing one or more additional parameters relating to network traffic observed on each of the plurality of network paths and flagging each of the plurality of network paths wherein the one or more additional parameters indicate a correlation with the transaction; and
assigning new probabilities to each of the plurality of network paths based on each of the re-executed transactions, wherein the new probability for each flagged path is increased and the new probability for each remaining path is decreased relative to the base probabilities.
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Accused Products
Abstract
Disclosed herein is a computer implemented technique for discovering the information technology resources that are involved in a particular networked business transaction. The system comprises three basic components. A robotic transaction playback client records the various steps in a particular transaction and can repetitively execute these steps to analyze the results. A network record collector observes the traffic throughout the network in response to the repeated instances of the transaction executed by the robotic transaction playback client. A backend processor analyzes the observations of network traffic to determine which ones are possibly tied to the transaction, and from this information determine which network components are part of the transaction being analyzed. Event timing information from a plurality of executions of a particular transaction are used to determine resource usage and paths.
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Citations
15 Claims
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1. A computer network system for identifying resources used in a network transaction, the system comprising:
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a plurality of computer systems communicatively coupled to a computer network; wherein one or more of the plurality of computers systems comprises a programmable processor and the programmable processor is configured to execute; a robotic transaction playback client configured to initiate re-execution of a recorded transaction; a network record collector; and a backend processor; wherein the backend processor performs identification analysis by analyzing newly collected data, the newly collected data being collected by the network record collector in response to one or more transactions re-executed by the robotic transaction playback client to identify one or more resources used in the one or more transactions, the identification analysis comprising; identifying a plurality of network paths potentially corresponding to the transaction; assigning equal base probabilities to each of the plurality of network paths; analyzing one or more additional parameters relating to network traffic observed on each of the plurality of network paths and flagging each of the plurality of network paths wherein the one or more additional parameters indicate a correlation with the transaction; and assigning new probabilities to each of the plurality of network paths based on each of the re-executed transactions, wherein the new probability for each flagged path is increased and the new probability for each remaining path is decreased relative to the base probabilities. - View Dependent Claims (2, 3, 4, 5)
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6. A computer network system for identifying network resources required by a transaction, the computer network system comprising:
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a plurality of computers communicatively coupled to a computer network; wherein one or more of the plurality of computers systems comprises a programmable processor and the programmable processor is configured to execute; recording the components of the transaction; initiating re-execution of the recorded transaction one or more times; collecting one or more data sets from a plurality of network probes wherein each of the one or more data sets uniquely corresponds to one re-execution of the recorded transaction; and analyzing the collected data sets to identify network resources required by the re-executed transaction wherein the analysis comprises; identifying a plurality of network paths potentially corresponding to the transaction; assigning equal base probabilities to each of the plurality of network paths; analyzing one or more additional parameters relating to network traffic observed on each of the plurality of network paths and flagging each of the plurality of network paths wherein the one or more additional parameters indicate a correlation with the transaction; and assigning new probabilities to each of the plurality of network paths based on each of the re-executed transactions, wherein the new probability for each flagged path is increased and the new probability for each remaining path is decreased relative to the base probabilities. - View Dependent Claims (7, 8, 9, 10, 11, 12, 13)
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14. A non-transitory machine readable medium, having embodied thereon instructions executable by one or more machines to cause the one or more machines to collectively:
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record the components of the transaction; initiate re-execution of the recorded transaction one or more times; collect one or more data sets from a plurality of network probes wherein each of the one or more data sets uniquely corresponds to one re-execution of the recorded transaction; and analyze the collected data sets to identify network resources required by the re-executed transaction wherein the analysis comprises; identifying a plurality of network paths potentially corresponding to the transaction; assigning equal base probabilities to each of the plurality of network paths; analyzing one or more additional parameters relating to network traffic observed on each of the plurality of network paths and flagging each of the plurality of network paths wherein the one or more additional parameters indicate a correlation with the transaction; and assigning new probabilities to each of the plurality of network paths based on each of the re-executed transactions, wherein the new probability for each flagged path is increased and the new probability for each remaining path is decreased relative to the base probabilities.
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15. A non-transitory machine readable medium, having embodied thereon instructions executable by one or more machines to cause the one or more machines to collectively execute:
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a robotic transaction playback client configured to initiate re-execution of a recorded transaction; a network record collector; and a backend processor; wherein the backend processor performs identification analysis by analyzing newly collected data, the newly collected data being collected by the network record collector in response to one or more transactions re-executed by the robotic transaction playback client to identify one or more resources used in the one or more transactions, the identification analysis comprising; identifying a plurality of network paths potentially corresponding to the transaction; assigning equal base probabilities to each of the plurality of network paths; analyzing one or more additional parameters relating to network traffic observed on each of the plurality of network paths and flagging each of the plurality of network paths wherein the one or more additional parameters indicate a correlation with the transaction; and assigning new probabilities to each of the plurality of network paths based on each of the re-executed transactions, wherein the new probability for each flagged path is increased and the new probability for each remaining path is decreased relative to the base probabilities.
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Specification