A Proportional Fair Backoff scheme for wireless sensor networks

This paper aims at improving the throughput of the wireless sensor networks (WSNs), particularly to overcome the so-called funneling effect for WSNs with converge-cast patterns. Due to the disproportionate larger number of packets accumulated in the sensors that are closer to the sink, there is a need to decrease the collisions and increase the throughput around the sink area as well as the nodes that experience a heavy pass-through traffic. In this paper, we proposed a new scheme, namely PFB (Proportional Fairness Backoff), which provides additional scheduling opportunities to nodes closer to the sink. The new scheme employs Kelly´s shadow price theory to achieve the proportional fairness, which takes advantage of the tree topology that is the de facto standard in today´s WSNs. In PFB, the size of backoff window is dynamically adjusted with respect to the height of nodes belong in the tree. With close-form analysis and extensive simulations, we show that PFB can achieve up to 100% throughput increase over the widely used CSMA when the network is highly loaded.