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The need for cross-layer information in access point selection algorithms
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Source Internet Measurement Conference archive
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement table of contents
Rio de Janeriro, Brazil
SESSION: Wireless table of contents
Pages: 257 - 262  
Year of Publication: 2006
ISBN:1-59593-561-4
Authors
Karthikeyan Sundaresan  Georgia Tech
Konstantina Papagiannaki  Intel Research Cambridge
Sponsors
SIGCOMM: ACM Special Interest Group on Data Communication
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 7,   Downloads (12 Months): 53,   Citation Count: 6
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ABSTRACT

The low price of commodity wireless LAN cards and access points (APs) has resulted in the rich proliferation of high density WLANs in enterprise, academic environments, and public spaces. In such environments wireless clients have a variety of affiliation options that ultimately determine the quality of service they receive from the network. The state of the art mechanism behind such a decision typically relies on received signal strength, associating clients to that access point (AP) in their neighborhood that features the strongest signal. More intelligent algorithms have been further proposed in the literature. In this work we take a step back and look into the fundamental metrics that determine end user throughput in 802.11 wireless networks. We identify three such metrics pertaining to wireless channel quality, AP capacity in the presence of interference, and client contention. We modify the low level software functionality (firmware and microcode) of a commercial wireless adaptor to measure the necessary quantities. We then test, in a real testbed, the ability of each metric to capture end user throughput through a range of diverse network conditions. Our experimental results indicate that user affiliation decisions should be based on metrics that do not only reflect physical layer performance, or network occupancy, but also concretely capture MAC layer behavior. Based on the acquired insight, we propose a new metric that is shown to be highly accurate across all tested network scenarios.


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
J. Allen. Joing proposal for 802.11e qos enhancements, February 2003. IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs).
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P. Clifford, K. Duffy, J. Foy, D. Leith, and D. Malone. Modeling 802.11e for data traffic parameter design. In WiOpt, April 2006.
 
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D. Larson, R. Murty, and E. Qi. An Adaptive Approach to Wireless Network Performance Optimization. Technology@Intel Magazine, feb/mar 2004.
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Cisco Systems. Deployment guide: Cisco aironet 1000 series lightweight access points.
 
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S. Vasudevan, K. Papagiannaki, C. Diot, J. Kurose, and D. Towsley. Facilitating Access Point Selection in IEEE 802.11 Wireless Networks. In ACM Sigcomm IMC, Berkeley, October 2005.

CITED BY  6

Collaborative Colleagues:
Karthikeyan Sundaresan: colleagues
Konstantina Papagiannaki: colleagues