P2P网络节点信息信任度计算模型仿真研究  

Research and Simulation on Information Trust Calculation Model of P2P Network Nodes

作　　者：蒋越[1] 

机构地区：[1]中国人民解放军92941部队

出　　处：《计算机仿真》2014年第1期298-301,共4页Computer Simulation

摘　　要：P2P网络系统中竹点持有信息的信任度评估是节点安全性能评估的重要指标,P2P网络中由于对中心节点较为依赖和节点频繁退出及加入,会造成的节点能量波动,造成传统的网络节点信任度计算出现偏差,提出了改进量子遗传算法的P2P网络节点信息信任模型。将P2P网络系统中节点信任度估计问题转化为从源节点到目的节点的最优信任路径寻优问题;对节点的可能信息传递路径进行染色体映射,计算其适应度值;然后利用改进的粒子群算法对量子旋转角度进行动态调整,依据个体信息熵和自适应变异算子迭代的进行最优个体和适应度值的搜索,输出节点信任关系解空间中的最优解。实验证明,改进算法具有较好的收敛速度和执行效率,且当节点跳级数较少时,可明显提高信任度计算的准确性。The trust evaluation of nodes information was an important index to evaluate the safety performance in P2P network system. An improved P2P network node information trust model was proposed based on quantum genetic algorithm. The P2P network node trust estimation problem was transformed into an optimization problem of optimal trust path from source node to destination node. The information transfer path was implemented with chromosome mapping. The fitness value was calculated. The improved particle swarm algorithm was used to dynamically adjust the quantum rotation angle. The individual information entropy and adaptive mutation operator iterative were used for searching the optimal individual and the fitness value. The optimal solution of node trust solution space was output- ted. Simulation result proves that the improved algorithm has better convergence speed and implementation efficiency. When the node skip is less, the accuracy of nodes trust degree calculation can be improved significantly.

关 键 词：量子遗传算法 信任度 粒子群算法 推荐信任 

分 类 号：TP256.6[自动化与计算机技术—检测技术与自动化装置]