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On the treeness of internet latency and bandwidth
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Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems table of contents
Seattle, WA, USA
SESSION: Traffic analysis table of contents
Pages 61-72  
Year of Publication: 2009
ISBN:978-1-60558-511-6
Authors
Venugopalan Ramasubramanian  Microsoft Research Silicon Valley, Mountain View, CA, USA
Dahlia Malkhi  Microsoft Research Silicon Valley, Mountain View, CA, USA
Fabian Kuhn  Massachusetts Institute of Technology, Cambridge, MA, USA
Mahesh Balakrishnan  Microsoft Research Silicon Valley, Mountain View, CA, USA
Archit Gupta  Data Domain Inc., Santa Clara, CA, USA
Aditya Akella  University of Wisconsin-Madison, Madison, WI, USA
Sponsors
ACM: Association for Computing Machinery
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
Publisher
ACM  New York, NY, USA
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ABSTRACT

Existing empirical studies of Internet structure and path properties indicate that the Internet is tree-like. This work quantifies the degree to which at least two important Internet measures--latency and bandwidth--approximate tree metrics. We evaluate our ability to model end-to-end measures using tree embeddings by actually building tree representations. In addition to being simple and intuitive models, these trees provide a range of commonly-required functionality beyond serving as an analytical tool.

The contributions of our study are twofold. First, we investigate the ability to portray the inherent hierarchical structure of the Internet using the most pure and compact topology, trees. Second, we evaluate the ability of our compact representation to facilitate many natural tasks, such as the selection of servers with short latency or high bandwidth from a client. Experiments show that these tasks can be done with high degree of success and modest overhead.


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.

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Collaborative Colleagues:
Venugopalan Ramasubramanian: colleagues
Dahlia Malkhi: colleagues
Fabian Kuhn: colleagues
Mahesh Balakrishnan: colleagues
Archit Gupta: colleagues
Aditya Akella: colleagues