ACM Home Page
Please provide us with feedback. Feedback
Measuring and characterizing end-to-end Internet service performance
Full text PdfPdf (1.46 MB)
Source ACM Transactions on Internet Technology (TOIT) archive
Volume 3 ,  Issue 4  (November 2003) table of contents
Pages: 347 - 391  
Year of Publication: 2003
ISSN:1533-5399
Authors
Ludmila Cherkasova  Hewlett-Packard Laboratories, Palo Alto, CA
Yun Fu  Duke University, Durham, NC
Wenting Tang  Hewlett-Packard Laboratories, Palo Alto, CA
Amin Vahdat  Duke University, Durham, NC
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 11,   Downloads (12 Months): 188,   Citation Count: 5
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues   peer to peer  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/945846.945849
What is a DOI?

ABSTRACT

Fundamental to the design of reliable, high-performance network services is an understanding of the performance characteristics of the service as perceived by the client population as a whole. Understanding and measuring such end-to-end service performance is a challenging task. Current techniques include periodic sampling of service characteristics from strategic locations in the network and instrumenting Web pages with code that reports client-perceived latency back to a performance server. Limitations to these approaches include potentially nonrepresentative access patterns in the first case and determining the location of a performance bottleneck in the second.This paper presents EtE monitor, a novel approach to measuring Web site performance. Our system passively collects packet traces from a server site to determine service performance characteristics. We introduce a two-pass heuristic and a statistical filtering mechanism to accurately reconstruct different client page accesses and to measure performance characteristics integrated across all client accesses. Relative to existing approaches, EtE monitor offers the following benefits: i) a latency breakdown between the network and server overhead of retrieving a Web page, ii) longitudinal information for all client accesses, not just the subset probed by a third party, iii) characteristics of accesses that are aborted by clients, iv) an understanding of the performance breakdown of accesses to dynamic, multitiered services, and v) quantification of the benefits of network and browser caches on server performance. Our initial implementation and performance analysis across three different commercial Web sites confirm the utility of our approach.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

1
 
2
Caceres, R., Duffield, N., Feldmann, A., Friedmann, J., Greenberg, A., Greer, R., Johnson, T., Kalmanek, C., Krishnamurthy, B., Lavelle, D., Mishra, P., Ramakrishnan, K., Rexford, J., True, F., and van der Merwe, J. 2000. Measurement and Analysis of IP Network Usage and Behaviour.
 
3
Candle Corporation: eBusiness Assurance. http://www.candle.com/.
 
4
Cardwell, N., Savage, S., and Anderson, T. 2000. Modeling TCP Latency. In INFOCOM.
 
5
Cisco Distributed Director. http://www.cisco.com/.
 
6
 
7
Fielding, R., Gettys, J., Mogul, J., Nielsen, H., and Berners-Lee, T. 2001. Hypertext Transfer Protocol---HTTP/1.1. Tech. Rep. RFC 2616, IETF. June.
 
8
Gomez, Inc. http://www.gomez.com.
 
9
 
10
HP Corporation. OpenView Products: Web Transaction Observer. http://www.openview.hp.com.
 
11
IBM Corporation. Tivoli Web Management Solutions. http://www.tivoli.com/products/demos/twsm.html.
 
12
IBM Research. Page Detailer. http://www.research.ibm.com/pagedetailer/.
 
13
JavaServer Pages. http://java.sun.com/products/jsp/technical.html.
 
14
JavaServlet Technology. http://java.sun.com/products/servlet/.
 
15
 
16
Keynote Systems, Inc. http://www.keynote.com.
 
17
Krishnamurthy, B. and Rexford, J. 1998. Software Issues in Characterizing Web Server Logs.
 
18
Krishnamurthy, B. and Rexford, J. 1999. En Passant: Predicting HTTP/1.1 Traffic.
 
19
20
21
 
22
23
24
 
25
NetMechanic, Inc. http://www.netmechanics.com.
 
26
NetQoS Inc. http://www.netqos.com.
27
 
28
Olshefski, D. P., Nieh, J., and Agrawal, D. 2001. Inferring Client Response Time at the Web Server. In Proceedings of USITS.
 
29
Porivo Technologies, Inc. http://www.porivo.com.
 
30
Rajamony, R. and Elnozahy, M. 2001. Measuring Client-Perceived Response Times on the WWW. In Proceedings of the Third USENIX Symposium on Internet Technologies and Systems (USITS).
 
31
Seshan, S., Stemm, M., and Katz, R. H. 1997. SPAND: Shared Passive Network Performance Discovery. In Proceedings of USITS.
32
 
33
Software Research Inc. http://www.soft.com.
 
34
Stemm, M., Katz, R. H., and Seshan, S. 2000. A Network Measurement Architecture for Adaptive Applications. In Proceedings of IEEE INFOCOM.
 
35
Tcpdump. http://www.tcpdump.org.


Collaborative Colleagues:
Ludmila Cherkasova: colleagues
Yun Fu: colleagues
Wenting Tang: colleagues
Amin Vahdat: colleagues

Peer to Peer - Readers of this Article have also read: