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Jigsaw: solving the puzzle of enterprise 802.11 analysis
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Source Applications, Technologies, Architectures, and Protocols for Computer Communication archive
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications table of contents
Pisa, Italy
SESSION: Wireless table of contents
Pages: 39 - 50  
Year of Publication: 2006
ISBN:1-59593-308-5
Also published in ...
Authors
Yu-Chung Cheng  University of California, San Diego, CA
John Bellardo  University of California, San Diego, CA
Péter Benkö  University of California, San Diego, CA
Alex C. Snoeren  University of California, San Diego, CA
Geoffrey M. Voelker  University of California, San Diego, CA
Stefan Savage  University of California, San Diego, CA
Sponsors
SIGCOMM: ACM Special Interest Group on Data Communication
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 39,   Downloads (12 Months): 173,   Citation Count: 24
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ABSTRACT

The combination of unlicensed spectrum, cheap wireless interfaces and the inherent convenience of untethered computing have made 802.11 based networks ubiquitous in the enterprise. Modern universities, corporate campuses and government offices routinely de-ploy scores of access points to blanket their sites with wireless Internet access. However, while the fine-grained behavior of the 802.11 protocol itself has been well studied, our understanding of how large 802.11 networks behave in their full empirical complex-ity is surprisingly limited. In this paper, we present a system called Jigsaw that uses multiple monitors to provide a single unified view of all physical, link, network and transport-layer activity on an 802.11 network. To drive this analysis, we have deployed an infrastructure of over 150 radio monitors that simultaneously capture all 802.11b and 802.11g activity in a large university building (1M+ cubic feet). We describe the challenges posed by both the scale and ambiguity inherent in such an architecture, and explain the algorithms and inference techniques we developed to address them. Finally, using a 24-hour distributed trace containing more than 1.5 billion events, we use Jigsaw's global cross-layer viewpoint to isolate performance artifacts, both explicit, such as management inefficiencies, and implicit, such as co-channel interference. We believe this is the first analysis combining this scale and level of detail for a production 802.11 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.

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CITED BY  24

Collaborative Colleagues:
Yu-Chung Cheng: colleagues
John Bellardo: colleagues
Péter Benkö: colleagues
Alex C. Snoeren: colleagues
Geoffrey M. Voelker: colleagues
Stefan Savage: colleagues