无线传感器网络中基于熵评判的关联支配集构造算法

摘要

无线传感器网络通常是密集分布的,因此相邻网络节点感知的数据之间具有很大的相关性.为了在无线传感器网络中进行数据冗余缩减,文中提出了一个基于熵评判的关联支配集构造算法(EECDS),算法首先通过评价高斯随机变量的熵值来判断网络节点间的数据相关性,然后分布式地构造一个关联图,最后根据关联图信息移除网络中的冗余节点,构建一个连通关联支配集.基于连通关联支配集的数据采集策略能在密集无线传感器网络中进行高效的数据冗余缩减,显著降低网络的能量消耗,延长网络的生命周期.%Wireless sensor networks are usually densely deployed, so the data sensed from neighboring sensor nodes is highly correlated. For redundancy removal in wireless sensor networks,this paper presents an algorithm named entropy evaluation for correlation dominating set construction (EECDS). The algorithm first determines the correlation degree between sensor nodes by evaluating the entropy of Gaussian random variables, and then distributively generates a correlation graph. Based on the correlation graph, the EECDS algorithm finally constructs a connected correlation dominating set by removing redundant sensor nodes. Data gathering policies with the help of connected correlation dominating sets will greatly reduce data redundancy of dense sensor networks, and therefore result in decrease of energy consumption and prolong lifetime of wireless sensor networks.