基于马尔可夫链的无线传感器网络分布式调度方法

能量效率是无线传感器网络(Wireless sensor network, WSN)研究中的核心问题之一. 当节点采用电池供电时, 有限的能量限制了网络的生存周期, 从而对无线传感器网络的大规模应用提出了挑战. 本文基于马尔可夫链, 提出了一种实用的、协作分布式的调度方法, 并从理论上证明了该方法的收敛性. 该方法不仅可对节点的休眠/唤醒进行调度, 还可以对节点数据发送进行调度以减少数据冲突的发生. 仿真实验结果表明, 该方法能够有效地减少节点能量的消耗, 且对其他网络性能的影响较小.

Markov Chain-based Distributed Scheduling Approach for Wireless Sensor Network

Energy efficiency is one of the core issues of wireless sensor network (WSN). For battery powered WSN, the energy constraint restricts the lifetime of WSN, which poses great challenges to its large scale application. In this paper, we propose a collaborative distributed scheduling approach based on Markov chain, which is applicable to real WSN. We prove that this approach is convergent. This approach can not only schedule wake-up and sleep states of nodes, but also schedule the data transmission of nodes to reduce the collision of data packets. The simulation results show that the proposed approach can save energy effectively and has less effect on other performances of the network.