网络不信任路径的高效搜索模型仿真分析

Network Distrust Efficient Search Model Simulation Analysis of the Path

网络路径搜索过程中,由于网络路径彼此独立与网络信息种类间不能直接建立关联,只根据源节点的信任值对网络不信任路径进行确定,忽略了网络不信任路径本身存在很多干扰,导致路径选择不准确,搜索效率低的问题。提出改进粒子群和蚁群算法的网络不信任路径的高效搜索模型,通过MPSO算法的实现节点间的信任度,利用改进粒子群算法对网络中初始解节点中的信息素进行增强处理后,利用蚁群算法增加网络不信任路径搜索过程的收敛性,并对最优解进行计算,利用计算结果对选择路径进行分析,同时对信息素进行更新,最终确定整个网络的不信任路径权重初始分布信息,对初始点进行重置,实现网络不信任路径的搜索。仿真实验结果表明,采用所提模型对网络不信任路径进行搜索效率高。

An efficient searching model for distrust path in the network based on particle swarm optimization and ant colony algorithm is proposed. Through the MPSO algorithm to achieve the degree of trust between nodes, the results of the particle swarm algorithm is obtained to enhance the pheromone on the node of the initial solution. By introducing the ant colony algorithm to accelerate convergence and approach the optimal solution, and analyzing the process of selecting path and updating pheromone, the initial distribution information of weight of the whole network＇s distrust path is determined, and the initial point is reset, so as to achieve the search of the distrust path in the network. The simulation results show that the proposed model for distrust path searching in network has high efficiency.