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A statistical framework for efficient monitoring of end-to-end network properties
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Source Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems table of contents
Banff, Alberta, Canada
POSTER SESSION: Posters table of contents
Pages: 390 - 391  
Year of Publication: 2005
ISBN:1-59593-022-1
Also published in ...
Authors
David Chua  Boston University
Eric D. Kolaczyk  Boston University
Mark Crovella  Boston University
Sponsors
ACM: Association for Computing Machinery
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 31,   Citation Count: 2
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ABSTRACT

Network service providers and customers are often concerned with aggregate performance measures that span multiple network paths. Unfortunately, forming such network-wide measures can be difficult, due to the issues of scale involved. As a result, it is of interest to explore the feasibility of methods that dramatically reduce the number of paths measured in such situations while maintaining acceptable accuracy.In previous work [4] we have proposed a statistical framework for efficiently addressing this problem. The key to our method lies in the observation and exploitation of the fact that network paths show significant redundancy (sharing of common links).We now make three contributions in [3]: (1) we generalize the framework to make it more immediately applicable to network measurements encountered in practice; (2) we demonstrate that the observed path redundancy upon which our method is based is robust to variation in key network conditions and characteristics, including the presence of link failures; and (3) we show how the framework may be applied to address three practical problems of interest to network providers and customers, using data from an operating network.


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
A. Akella, S. Seshan, and A. Shaikh. Multihoming performance benefits: An experimental evaluation of practical enterprise strategies. In USENIX, 2004.
2
 
3
D. B. Chua, E. D. Kolaczyk, and M. Crovella. A statistical framework for efficient monitoring of end-to end network properties. http://arxiv.org/abs/cs.NI/0412037.
 
4
D. B. Chua, E. D. Kolaczyk, and M. Crovella. Efficient estimation of end-to-end network properties. In Proceedings of IEEE INFOCOM 2005, 2005.
 
5
Y. Shavitt, X. Sun, A. Wool, and B. Yener. Computing the unmeasured: An algebraic approach to internet mapping. In IEEE INFOCOM 2001, April 2001.


Collaborative Colleagues:
David Chua: colleagues
Eric D. Kolaczyk: colleagues
Mark Crovella: colleagues