DOI: 10.3724/SP.J.1016.2011.01214

Chinese Journal of Computers (计算机学报) 2011/34:7 PP.1214-1223

Channel Selection Algorithm Based on Gibbs Sampler for Optimal QoM in Multi-Channel Wireless Networks

In wireless networks, wireless nodes are distributed in a region to monitor the activities of users. It can be used for fault diagnosis, resource management and critical path analysis. Due to the constraint of hardware, wireless nodes can only collect information on one channel at a time. Therefore, it is a key issue to optimize the channel selection for nodes to maximize the information collected, so as to maximize the Quality of Monitoring (QoM) for wireless networks. In this paper, the authors propose a distributed channel selection algorithm based on Gibbs Sampler, and according to the optimization objective, design an energy function to calculate the selection probability of each channel. The optimized channel selection can be achieved according to the former probabilities. This algorithm is with low complexity and provable convergence performance. Experiments show that the proposed algorithm can optimize the QoM of wireless networks in distributed manner, and the quality of solutions can approach the performance of centralized algorithms.

Key words:Internet of Things,multi-channel wireless networks,channel selection,quality of monitoring,Gibbs sampler,energy function

ReleaseDate:2014-07-21 15:53:31

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