Optimization Algorithm Based on SPSA in Multi-channel Multi-radio Wireless Monitoring Network

In wireless monitoring networks, multi-radio wireless sniffers are distributed for capturing and analyzing user activities in order to realize network monitoring, fault diagnosis, resource management, etc. Therefore, it is a key topic to optimize the channel selection for sniffers to maximize the information collected, so as to maximize the Quality of Monitoring (QoM) of the network. In this paper, a simultaneous perturbation stochastic approximation (SPSA)-based solution is proposed in order to realize optimal channel selection. During iteration process, random perturbation strategy is used to compute the approximate gradient of the objective function, which can lead the searching to the optimal solution. The algorithm is fast in convergence and low in complexity, and is very suitable for multi-dimension optimization problem. Extensive experimental results with comparison demonstrate that the proposed algorithm can realize the multi-channel multi-radio selection in wireless monitoring networks with high QoM performance.