基于信誉机制的分布式扩散最小均方算法  

Distributed Diffusion Least Mean Square Algorithm Based on the Reputation Mechanism

作　　者：卢光跃[1] 陈文晓[1] 黄庆东[1] 

机构地区：[1]西安邮电大学无线网络安全技术国家工程实验室,西安710121

出　　处：《电子与信息学报》2015年第5期1234-1240,共7页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(61271276;61301091);陕西省国际合作项目(2013KW01-03);工业和信息化部通信软科学项目(2014R33);陕西省自然科学基金(2014JM8299)资助课题

摘　　要：非安全环境中的无线传感器网络(WSN)可能存在恶意攻击节点,恶意节点将会篡改其观测数据以影响参数估计的准确性。为此,该文提出基于信誉机制的分布式扩散最小均方(R-d LMS)算法和扩散归一化最小均方(R-d NLMS)算法。该算法能够根据各节点对整个网络参数估计的贡献来设置相应的信誉值,从而减小恶意节点对网络攻击的影响。仿真结果表明,与无信誉值的算法相比,该算法的性能得到大幅度提高,且R-d NLMS算法在R-d LMS算法的基础上,算法性能得到进一步提升。To deal with the problem of signal estimation for Wireless Sensor Networks （WSN） in a untrustworthy environment where malicious nodes tamper the measured data, two reputation-based Mgorithms, that are, Reputation-based diffusion Least Mean Square （R-dLMS） algorithm and Reputation-based diffusion Normalized Least Mean Square （R-dNLMS） algorithm, are proposed. The proposed algorithms could assign the appropriate reputation value to each node according to its contribution to the whole network, and minimize the reputation value of malicious nodes to lower the impact of malicious nodes in the network. Simulation results show that the proposed algorithms can greatly improve the performance compared with the one without reputation value, and the performance of R-dNLMS algorithm has been further improved based on R-dLMS algorithm.

关 键 词：无线传感器网络 恶意攻击 分布式 扩散最小均方 信誉值 

分 类 号：TP393[自动化与计算机技术—计算机应用技术] TN911.7[自动化与计算机技术—计算机科学与技术]