Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8115
Title: Self-tuned distributed monitoring of multi-channel wireless networks using Gibbs sampler
Authors: Wang, Y
Zheng, R
Wang, Q 
Keywords: Channel assignment
Distributed sniffer
Gibbs sampler
Wireless side network monitoring
Issue Date: 2014
Publisher: Elsevier Science Bv
Source: Computer networks, 2014, v. 64, p. 261-272 How to cite?
Journal: Computer Networks 
Abstract: Wireless side monitoring employing distributed sniffers has been shown to complement wired side monitoring using Simple Network Management Protocol (SNMP) and base station logs, since it reveals detailed PHY and MAC behaviors, as well as timing information. Due to hardware limitations, wireless sniffers typically can only collect information on one channel at a time. Distributed algorithms are desirable to determine the optimal channel allocation of sniffer nodes to maximize the information collected. In this paper, we propose Gibbs sampler based algorithms for robust distributed monitoring of multi-channel wireless networks. Among several variants of the base Gibbs sampling approach, we find that most algorithms suffer from high sensitivity to parameter selection. In contrast, Gibbs sampling using a thermodynamic schedule is self-tuned and can adapt to different network configurations. Simulation studies show that the proposed algorithms can achieve faster convergence rate and have higher chance of reaching global optima than traditional Gibbs sampler algorithm.
URI: http://hdl.handle.net/10397/8115
ISSN: 1389-1286
DOI: 10.1016/j.comnet.2014.02.014
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