A Preventive Traffic Adaptation Model for Wireless Mesh Networks Using Fuzzy Logic

Nowadays, real time traffic over wireless networks is increasing sharply. In addition, network scale is larger due to new facilities as offered by wireless mesh networks. However, the differences between (1) the infrastructure capacities, (2) the end users devices technologies, (3) the number of users, and (4) the number of real time applications are implying the need of more dynamic quality of service (QoS) models. Traditional QoS models are not always suitable to fill out the gap between the four cited points. We are mentioning more QoS degradation due to network congestion. Therefore, in this paper, we propose a novel, dynamic and persistent traffic adaption model, called FTAM. Its main role is to avoid as maximum as possible network congestion. FTAM is based on the fuzzy logic, which is known by its dynamicity and efficiency in uncertain environment. By monitoring the nodes queues evolution, FTAM estimates network congestion and makes the suitable traffic adaptation step. Extensive simulations have proved the efficiency of FTAM in terms of real time traffic QoS guarantee and preventive congestion control.