A fuzzy priority based congestion control scheme in wireless body area networks

Congestion management is one of the major challenges in wireless body area network (WBAN) applications. This study proposes a technique similar to the random early detection (RED) active queue management (AQM) to indicate congestion. A two-input-single-output fuzzy logic system is used to dynamically adjust the maximum drop probability (maxp) parameter of the RED algorithm, then two adaptive values the minimum threshold (minth) and the maximum threshold (maxth) are used to estimate the congestion level of each sensor nodes. We adjust send rate of the parent node with a fuzzy logical controller (FLC) based on the child's node traffic load, considering the different amounts of data being transmitted. The simulation results show that the proposed protocol achieves high performance as compared to PCCP and PHTCCP, in terms of packet loss, end-to-end delay and energy.