Optimal QoM in Multichannel Wireless Networks Based on MQICA

Abstract

In wireless networks, wireless sniffers are distributed in a region to monitor the activities of users. It can be applied for fault diagnosis, resource management, and critical path analysis. Due to hardware limitations, wireless sniffers typically can only collect information on one channel at a time. 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) for wireless networks. In this paper, a Multiple-Quantum-Immune-Clone-Algorithm- (MQICA-) based solution was proposed to achieve the optimal channel allocation. The extensive simulations demonstrate that MQICA outperforms the related algorithms evidently with higher monitoring quality, lower computation complexity, and faster convergence. The practical experiment also shows the feasibility of this algorithm.