WSNs中基于节点信任度的机会路由算法  

Node Trust based Opportunistic Routing in Wireless Sensor Networks

作　　者：杜可怡 苏凡军[1] DU Ke-yi;SU Fan-jun(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院

出　　处：《软件导刊》2019年第6期70-74,79,共6页Software Guide

基　　金：国家自然科学基金项目(61703278)

摘　　要：针对机会路由的候选转发集中存在恶意节点导致网络性能下降问题,提出一种计算节点信任度的评估模型。使用贝叶斯公式计算节点的直接信任度,根据节点的代数连通度得到间接信任度,利用信息熵的概念得到综合信任度。为高效辨别出候选转发集中的恶意节点,预先设定信任度阈值β。提出一种基于节点信任度的机会路由算法TBOR。TBOR利用信任模型初始化候选集中每个节点的综合信任度,再利用信任度阈值判断潜在的恶意节点,并将信任度大于信任度阈值的节点添加到候选转发集。实验结果表明,TBOR能高效识别并剔除候选转发集中的恶意节点,具有较高的检测率,保证了数据可靠传输。Aiming at the problem of network performance degradation caused by malicious nodes in the candidate forwarding of oppor-tunistic routing,an evaluation model for computing node trust is proposed. The Bayesian formula is used to calculate the direct trust de-gree of the node,and the indirect trust degree is obtained according to the algebraic connectivity of the node,and the concept of infor-mation entropy is used. In order to efficiently identify malicious nodes in the candidate forwarding set,the trust threshold β is preset. A Node Trust based opportunistic routing in wireless sensor networks(TBOR)is proposed. The TBOR uses the trust model to initialize the comprehensive trust degree of each node in the candidate set,and then uses the trust threshold to determine the potential malicious node,and adds the node with the trust degree greater than the trust threshold to the candidate forwarding set. The experimental results show that TBOR can effectively identify and eliminate malicious nodes in the candidate forwarding set,which has a high detection rate and ensures reliable data transmission.

关 键 词：机会路由 信任模型 代数连通度 信任度 无线传感器网络 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]