|
Author(s):
|
Yuanfang Chen, Dalian University of Technology ; Yuanfang Chen, School of Software; Mingchu Li, Dalian University of Technology; Lei Wang, Dalian University of Technology; Lei Shu, National University of Ireland
|
|
Abstract:
|
This paper aims at improving the throughput of the sensor networks, particularly to overcome the so-called funneling effect for sensor networks 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 method, namely PFB (Proportional Fair Backoff), which assures greater channel access to the nodes closer to the sink. The new method 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 sensor networks. In PFB, the size of backoff window is dynamically adjusted with respect to a node's height 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.
|
