基于多粒度和激励机制的移动P2P网络动态信任模型  

Dynamic Trust Model Based on Multiple Granularity and Incentive Mechanism for Mobile P2P Network

作　　者：王焱[1] 周天宏[2] 

机构地区：[1]郧阳师范高等专科学校教育系,湖北十堰442000 [2]武汉商业服务学院信息工程系,湖北武汉430056

出　　处：《实验室研究与探索》2013年第11期246-250,共5页Research and Exploration In Laboratory

基　　金：湖北省教育厅基金项目(2012Q003)

摘　　要：针对移动P2P网络高度动态性的特点,提出了一种基于多粒度和激励机制的动态信任模型。该模型选取用户关注的重要粒度参与直接信任值的计算,并根据历史交易情况引入激励机制对节点进行奖励和惩罚,通过推荐因子提高间接信任值的准确性,利用动态更新因子增加信任评估的动态适应能力。理论分析和仿真实验表明,该模型表现出较好的适应性、灵敏性与有效性,提高了交易成功率。Aiming at the highly dynamic features of mobile P2P network, a multiple granularity and incentive mechanism dynamic trust model is presented. With this model the calculation of direct trust value depends on the user attention granularity, at the same time the node rewards and punishment by the introduction of incentive mechanism, the improvement of indirect trust value accuracy by the recommended factor. Additionally, the dynamic update factor increases trust evaluation dynamic adaptability. Theoretical analyses and experimental results demonstrate that MGAIM_ DTM shows more adaptability, sensitivity and effectiveness, and can improve transaction success rate.

关 键 词：移动P2P 信任模型 激励机制 多粒度 交易 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]