Bayesian cognitive trust model based self-clustering algorithm for MANETs  

作　　者：WANG Wei1,2,3 & ZENG GuoSun1,2,31Department of Computer Science & Technology, Tongji University, Shanghai 200092, China 2Tongji Branch, National Engineering & Technology Center of High Performance Computer, Shanghai 200092, China 3Key Loboratory of Embedded System and Service Computing, Ministry of Education, Shanghai 200092, China 

出　　处：《Science China(Information Sciences)》2010年第3期494-505,共12页中国科学（信息科学）（英文版）

基　　金：supported by the National High-Tech Research & Development Program of China (Grant Nos.2007AA01Z425, 2009AA012201);the National Basic Research Program of China (Grant No. 2007CB316502);the National Natural Science Foundation of China (Grant Nos. 90718015, 70903051);the joint of NSFCand Microsoft Asia Research (Grant No. 60970155);the Ph.D. Programs Foundation of Ministry of Education(Grant No. 20090072110035);the Program of Shanghai Subject Chief Scientist (Grant No. 10XD1404400);the State Key Laboratory of High-end Server & Storage Technology (Grant No. 2009HSSA06);Program for Young Excellent Talents in Tongji University (Grant Nos. 0800219105, 2009KJ030)

摘　　要：With the introduction of mobile Ad hoc networks （MANETs）, nodes are able to participate in a dynamic network which lacks an underlying infrastructure. Before two nodes agree to interact, they must trust that each will satisfy the security and privacy requirements of the other. In this paper, using the cognition inspired method from the brain informatics （BI）, we present a novel approach to improving the search efficiency and scalability of MANETs by clustering nodes based on cognitive trust mechanism. The trust relationship is formed by evaluating the level of trust using Bayesian statistic analysis, and clusters can be formed and maintained autonomously by nodes with only partial knowledge. Simulation experiments show that each node can form and join proper clusters, which improve the interaction performance of the entire network. The essence of the underlying reason is analyzed through the theory of complex networks, revealing great scalability of this method.With the introduction of mobile Ad hoc networks （MANETs）, nodes are able to participate in a dynamic network which lacks an underlying infrastructure. Before two nodes agree to interact, they must trust that each will satisfy the security and privacy requirements of the other. In this paper, using the cognition inspired method from the brain informatics （BI）, we present a novel approach to improving the search efficiency and scalability of MANETs by clustering nodes based on cognitive trust mechanism. The trust relationship is formed by evaluating the level of trust using Bayesian statistic analysis, and clusters can be formed and maintained autonomously by nodes with only partial knowledge. Simulation experiments show that each node can form and join proper clusters, which improve the interaction performance of the entire network. The essence of the underlying reason is analyzed through the theory of complex networks, revealing great scalability of this method.

关 键 词：trust model MANET self-clustering Bayesian method cognitive mobile 

分 类 号：TN915[电子电信—通信与信息系统]