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A novel association algorithm for congestion relief in IEEE 802.11 WLANs
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Source International Conference On Communications And Mobile Computing archive
Proceedings of the 2006 international conference on Wireless communications and mobile computing table of contents
Vancouver, British Columbia, Canada
SESSION: T3-D: WAN's and PAN's symposium table of contents
Pages: 725 - 730  
Year of Publication: 2006
ISBN:1-59593-306-9
Authors
Ozgur Ekici  University of Ottawa, Ottawa, Ontario, Canada
Abbas Yongacoglu  University of Ottawa, Ottawa, Ontario, Canada
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Many wireless local area network (WLAN) performance estimations are done with the assumption of uniformly distributed stations (STAs). In practice, on the contrary STAs are distributed unevenly among access points (APs), causing hot-spots and under utilized APs in a wireless network. Considering a WLAN is made up of multiple APs, having some APs carrying excessive loads (i.e. hot-spots) degrades both the considered APs as well as the overall network performance. The system performance can be improved by associating incoming STAs effectively throughout the network, in a sense to balance the network load evenly between APs and relieve the hot-spot congestion. Currently employed user association method in IEEE 802.11 WLANs considers only the received signal strength of APs at STAs, and associates STAs to the closest (in signal strength sense) AP, ignoring its load and interference value.Novel user association algorithms are required for congestion relief and network performance improvement. In this work, a new distributed association algorithm taking into consideration not only the received signal strength of the APs at STAs but also AP loadings and interference is proposed. A new AP load calculation method acknowledging the interference between STAs and APs is presented. Our simulations demonstrate that the proposed algorithm can improve the overall system throughput performance more than 50% and offers a better load distribution across the network compared to conventional association algorithm.


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:
Ozgur Ekici: colleagues
Abbas Yongacoglu: colleagues