基于综合支持度的WSN节点分类方法

簇中节点分类管理对于提高无线传感器网络的性能至关重要。基于此，提出一种基于综合支持度的传感器节点分类方法，其核心是利用误差函数和模糊关联函数获取节点感知数据的综合支持度，并结合综合支持度的增量，将节点及其感知数据划分为可靠和不可靠 2类，为准确实施冗余节点和不可靠节点的行为控制提供可行性。仿真结果表明该方法能够有效地实施节点分类。

Node Classification Method Based on Integrative Support Degree in WSN

Node management of cluster is very important to the performance of Wireless Sensor Networks(WSN), so a method based on the integrative support degree is presented. The key of method is that the integrative support degree of sensing data is obtained with the error function and fuzzy correlation function, and sensor nodes and their sensing data are divided into two types of reliable and unreliable through their integrative support degrees and increments of integrative support degrees, which provide the feasibility for exact controlling the redundant nodes and unreliable nodes. Simulation results demonstrate that the method is efficient to realize sensor node classification.