A Stochastic Serving MPP Selection Method for Increasing the Efficiency of a Wireless Mesh Network

Since traffic is aggregated to a MPP that acts as an Internet gateway, if traffic load is not balanced among the MPPs in a WMN, the overall performance of a WMN becomes poor even though the total traffic load is far below the capacity of the WMN. Therefore, in this paper, we propose a stochastic load balancing scheme where each MP (Mesh Point) probabilistically selects its serving MPP according to the congestion levels of MPPs. Through extensive simulations using ns-2, we have verified that our scheme can stabilize a WMN fast when congestion occurs and reduce packet loss rate by distributing traffic load of a congested MPP to multiple MPPs in the inverse proportional to their congestion levels. Compared to queue-based load balancing scheme, our method can decrease network stabilization time by 34 seconds, and reduce packet loss rate by 7.6%. Since the proposed scheme can reduce network stabilization time by efficiently using network resource, it is expected to contribute to the reliable operation of a WMN.