Isolating local performance variation in website monitoring

• US 7,814,202 B2
• Filed: 06/05/2009
• Issued: 10/12/2010
• Est. Priority Date: 06/01/2005
• Status: Expired due to Fees

• Current Assignee: Neustar Incorporated
• Original Assignee: Neustar Incorporated
• Inventors: Drees, Timothy P., Taylor, Doug J., Rachitsky, Lenny
• Primary Examiner(s): WON, MICHAEL YOUNG
• Application Number:
  US12/479,152
• Publication Number:
  US 20090240805A1
• Time in Patent Office: 494 Days
• Field of Search: 709/202, 709/223, 709/203, 709/224
• US Class Current: 709/224
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 2201/865 Monitoring of software
• CPC Class Codes: G06F 2201/875 Monitoring of systems including the internet
• CPC Class Codes: G06F 2201/88 Monitoring involving counting

Abstract

Systems and methods are provided for isolating performance variation in website monitoring. A set of geographically diverse monitoring agents are identified and a subset of baseline agents is selected from these monitoring agents. The baseline agents are those agents that are geographically close to the target website or otherwise enjoy reliable communications with the target website and are therefore less affected by network latencies. The frequency at which a target website is monitored is weighted in favor of the baseline agents in order to get an accurate baseline metric for the target website while also obtaining information regarding global accessibility of the website from the geographically disperse monitoring agents. The variations in sample frequency can be optimized for each particular set of baseline agents. The set of baseline agents can be pre-assigned or dynamically identified based on an analysis of the performance variation from each of the monitoring agents.

Claims

1. A computer implemented method for isolating local performance variation in monitoring a target website from a monitoring server that is communicatively coupled with the target website via a data communication network, comprising:

identifying a target website to be monitored;

determining at least two proximity zones for the target website;

selecting a set of baseline agents where each baseline agent is in a first proximity zone that is closest to the target website;

selecting a set of monitor agents where each monitor agent is in a proximity zone other than the first proximity zone;

monitoring the target website in a plurality of monitoring rounds, wherein each monitoring round comprises monitoring the target website from each baseline agent and from at least one monitor agent; and

compiling a monitor report for the target website based on increased monitoring from said baseline agents relative to the monitoring from said monitor agents.

2. The method of claim 1, wherein the at least two proximity zones are determined geographically.

3. The method of claim 1, wherein the at least two proximity zones are determined based on network latency.

4. The method of claim 1, wherein the at least two proximity zones are determined based on packet round trip time.

5. The method of claim 1, wherein selecting a set of baseline agents comprises identifying those agents having the most reliable responses to a series of network communication tests with the target website.

6. The method of claim 5, wherein the most reliable responses are those responses having the fastest network round trip time.

7. The method of claim 5, wherein the most reliable responses are those responses having the least performance variation in website load time.

8. A computer readable medium having stored thereon one or more sequences of instructions for causing one or more microprocessors to perform the steps for isolating local performance variation in monitoring a target website, the steps comprising:

identifying a target website to be monitored;

determining at least two proximity zones for the target website;

selecting a set of baseline agents where each baseline agent is in a first proximity zone that is closest to the target website;

selecting a set of monitor agents where each monitor agent is in a proximity zone other than the first proximity zone;

monitoring the target website in a plurality of monitoring rounds, wherein each monitoring round comprises monitoring the target website from each baseline agent and from at least one monitor agent; and

compiling a monitor report for the target website based on increased monitoring from said baseline agents relative to the monitoring from said monitor agents.

9. The method of claim 8, wherein the at least two proximity zones are determined geographically.

10. The method of claim 8, wherein the at least two proximity zones are determined based on network latency.

11. The method of claim 8, wherein the at least two proximity zones are determined based on packet round trip time.

12. The method of claim 8, wherein selecting a set of baseline agents comprises identifying those agents having the most reliable responses to a series of network communication tests with the target website.

13. The method of claim 12, wherein the most reliable responses are those responses having the fastest network round trip time.

14. The method of claim 12, wherein the most reliable responses are those responses having the least performance variation in website load time.

15. A computer implemented method for isolating local performance variation in monitoring a target website from a monitoring server that is communicatively coupled with the target website via a data communication network, comprising:

identifying a target website to be monitored;

identifying a plurality of monitor agents dispersed across at least two proximity zones for the target website;

monitoring the target website in a plurality of monitoring rounds, wherein each monitoring round comprises monitoring the target website from each of the plurality of monitor agents;

determining a performance variation for each of at least a portion of the plurality of monitor agents; and

compiling a monitor report based on the determined performance variation of the at least a portion of the plurality of monitor agents.

16. The method of claim 15, wherein determining the performance variation of a first monitor agent comprises analysis of historical monitoring performance for the first monitor agent.

17. The method of claim 15, wherein determining the performance variation of a first monitor agent comprises identifying an average load time of a web page from the target website by the first monitor agent.

18. The method of claim 17, wherein determining the performance variation of a first monitor agent further comprises identifying a difference between the load time of the web page from the target website during a first monitoring round and the average load time of the web page.