Fuzzy logic congestion control in IEEE 802.11 wireless local area networks: A performance evaluation

Abstract

In 802.11 Wireless Local Area Networks, the wired and the wireless interfaces of the Access Point are characterized by the disparity in channel capacity. This presents a significant bottleneck for traffic flowing from the wired network to the wireless network. Therefore, the implementation of a congestion control mechanism in Access Points promises to be a suitable solution. Recently, a particle swarm optimized Fuzzy Logic Congestion Detection (FLCD) was proposed for IP networks. This algorithm synergistically combines the good characteristics of traditional Active Queue Management (AQM) algorithms and fuzzy logic based AQM algorithms. Its membership functions are designed automatically by using a Multi-objective Particle Swarm Optimization (MOPSO) algorithm in order to achieve optimal performance on all the major performance metrics of IP congestion control. In this paper, the authors evaluate the performance of the FLCD algorithm in the Wireless Local Area Network environment. They compare its performance with that of ARED and the Droptail mechanism. Simulation results show that the FLCD algorithm helps to minimize UDP traffic delay, packet loss rates. In terms of throughput, the FLCD algorithm exhibits similar performance to the other schemes. Its UDP jitter is slightly higher than that of the Droptail mechanism but better than that of ARED.