Sniffer channel selection for monitoring wireless LANs

  • Authors:

  • Xian Chen;Yoo-Ah Kim;Bing Wang;Yuan Song;Hieu Dinh;Guanling Chen

  • Affiliations:

  • Computer Science & Engineering Department, University of Connecticut, United States;National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, United States;Computer Science & Engineering Department, University of Connecticut, United States;Computer Science & Engineering Department, University of Connecticut, United States;Computer Science & Engineering Department, University of Connecticut, United States;Computer Science Department, University of Massachusetts, Lowell, United States

  • Venue:
  • Computer Communications
  • Year:
  • 2012

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Abstract

Wireless sniffers are often used to monitor access points (APs) in wireless LANs (WLANs) for network management, fault detection, and traffic characterization. It is cost effective to deploy single-radio sniffers that can monitor multiple nearby APs. To achieve this, a sniffer needs to switch among multiple channels since these APs often operate on orthogonal channels. In this paper, we formulate and solve two optimization problems on sniffer channel selection. Both problems require that each AP be monitored by at least one sniffer. In addition, one optimization problem requires minimizing the maximum number of channels that a sniffer listens to, and the other requires minimizing the total number of channels that the sniffers listen to. We prove that both optimization problems are NP-hard. For each problem, we propose three algorithms to solve it, one based on integer programming (IP), one based on LP-relaxation, and the third based on a greedy heuristic. We evaluate the performance of the various algorithms using two real-world datasets. Our results show that, for each problem, all the three algorithms are effective in achieving their optimization goals, and overall, the LP-based algorithm outperforms the other two algorithms.