AP Association for Proportional Fairness in Multirate WLANs

  • Authors:

  • Wei Li;Shengling Wang;Yong Cui;Xiuzhen Cheng;Ran Xin;Mznah A. Al-Rodhaan;Abdullah Al-Dhelaan

  • Affiliations:

  • Department of Computer Science, The George Washington University, Washington DC, USA;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Department of Computer Science, Tsinghua University, Beijing, P. R. China;Department of Computer Science, The George Washington University, Washington DC, USA;Department of Computer Science, Illinois Institute of Technology, Chicago, USA;College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia;College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

  • Venue:
  • IEEE/ACM Transactions on Networking (TON)
  • Year:
  • 2014

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Abstract

In this paper, we investigate the problem of achieving proportional fairness via access point (AP) association in multirate WLANs. This problem is formulated as a nonlinear programming with an objective function of maximizing the total user bandwidth utilities in the whole network. Such a formulation jointly considers fairness and AP selection. We first propose a centralized algorithm Non-Linear Approximation Optimization for Proportional Fairness (NLAO-PF) to derive the user–AP association via relaxation. Since the relaxation may cause a large integrality gap, a compensation function is introduced to ensure that our algorithm can achieve at least half of the optimal in the worst case. This algorithm is assumed to be adopted periodically for resource management. To handle the case of dynamic user membership, we propose a distributed heuristic Best Performance First (BPF) based on a novel performance revenue function, which provides an AP selection criterion for newcomers. When an existing user leaves the network, the transmission times of other users associated with the same AP can be redistributed easily based on NLAO-PF. Extensive simulation study has been performed to validate our design and to compare the performance of our algorithms to those of the state of the art.