Mobile and Ubiquitous Systems: Computing, Networking, and Services. 7th International ICST Conference, MobiQuitous 2010, Sydeny, Australia, December 6-9, 2010, Revised Selected Papers

Research Article

Virtualization for Load Balancing on IEEE 802.11 Networks

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  • @INPROCEEDINGS{10.1007/978-3-642-29154-8_20,
        author={Tib\^{e}rio Oliveira and Marcel Silva and Kleber Cardoso and Jos\^{e} Rezende},
        title={Virtualization for Load Balancing on IEEE 802.11 Networks},
        proceedings={Mobile and Ubiquitous Systems: Computing, Networking, and Services. 7th International ICST Conference, MobiQuitous 2010, Sydeny, Australia, December 6-9, 2010, Revised Selected Papers},
        proceedings_a={MOBIQUITOUS},
        year={2012},
        month={10},
        keywords={Wireless networks scheduling 802.11 association control},
        doi={10.1007/978-3-642-29154-8_20}
    }
    
  • Tibério Oliveira
    Marcel Silva
    Kleber Cardoso
    José Rezende
    Year: 2012
    Virtualization for Load Balancing on IEEE 802.11 Networks
    MOBIQUITOUS
    Springer
    DOI: 10.1007/978-3-642-29154-8_20
Tibério Oliveira1,*, Marcel Silva1,*, Kleber Cardoso2,*, José Rezende1,*
  • 1: Universidade Federal do Rio de Janeiro
  • 2: Universidade Federal de Goiás
*Contact email: tiberio@gta.ufrj.br, marcel@gta.ufrj.br, kleber@inf.ufg.br, rezende@gta.ufrj.br

Abstract

In IEEE 802.11 infrastructure networks composed by multiple APs, before a station can access the network it needs to make a decision about which AP to associate with. Usually, legacy 802.11 stations use no more than the signal strength of the frames received from each AP to support their decision. This can lead to an unbalanced distribution of stations among the APs, causing performance and unfairness problems. This work proposes a new approach that combines the number of associated stations and the current load of each AP plus the virtualization of client wireless interfaces. In this approach, stations frequently switch of association among APs and stay on each one of them for a time interval that is calculated based on the number of associated stations and the channel current load. Simulation results confirm the improvement obtained in the load balancing and fairness on network capacity allocation, while keeping the maximum network utilization.