基于Bayes与多层Bayes估计的WSN链路选择算法

Link selection algorithm for wireless sensor networks based on Bayesian and hierarchical Bayesian estimation

无线传感器网络(WSN)节点能量有限,采用传统的链路选择的方法(经验法)进行链路选择,需要发送大量的数据包作为测试样本,这在WSN中是不合适的。设计了两种基于Bayes估计与一种基于多层Bayes估计的WSN链路选择算法,分别记为BLSP-B1、BLSP-B2、BLSP-HE。仿真实验发现,在小样本的条件下,BLSP-B1、BLSP-B2、BLSP-HE选择高质量的链路的概率比经验法要高出10%～20%,其中BLSP-HE算法最稳健,性能较好。

The energy of nodes of wireless sensor networks is limited, using traditional link selection algorithm （empirical-algorithm） needs to send many data packets as testing samples, but it is not allowed in wireless sensor networks. The paper designs two link-selection algorithms based on Bayesian estimation and one link-selection algorithm based on hierarchical Bayesian estimation, marked as BLSP-B 1, BLSP-B2 and BLSP-HE. Simulation result shows that BLSP-B1, BLSP-B2 and BLSP-HE have a 10%-20% higher success rate than empirical-algorithm in selecting the high quality link in the case of the small sample. Among them, BLSP-HE has better and most robust performance.