SMAC-based proportional fairness backoff scheme in wireless sensor networks

This paper aims at mitigating the so-called Funneling Effect for S-MAC, particularly by improving the throughput and fairness of S-MAC. Wireless sensor networks (WSNs) exhibit some phenomenon named Funneling Effect resulting from the accumulation of disproportionate large number of packets in the regions close to the sink. The collision and congestion due to the Funneling Effect strongly weaken the vitality and robustness of WSNs. As for S-MAC which achieves great energy efficiency, the mitigation of funneling effect seems more significant and urgent. In this paper, targeted to alleviate the funneling effect for S-MAC, we propose a SMAC-based proportional fairness backoff scheme (SPFB). Based on the schedule and contention scheme in S-MAC, SPFB employs Kelly's shadow price theory to achieve the proportional fairness as well as optimizes the back off mechanism to improve the throughput. The contention window range is dynamically adjusted according to the load of individual node. With extensive simulations, we can show that SPFB can achieve much higher throughput than traditional S-MAC, especially when the network is heavy loaded. SPFB can also gain good energy efficiency.