进化算法迭代优化的P2P网络信任模型研究
发布时间：2019-07-03 20:10
【摘要】：为了解决P2P网络系统中节点频繁退出和加入引起的系统数据信息误差,并针对数据获取对中心节点依赖度较大和系统中节点的数据信息获取不完整等问题,提出了进化算法迭代优化的P2P网络信任模型。首先将P2P网络系统中节点数据信息获取的系统信任度估计模型转化为从源节点到目标节点最优信任关系的路径寻优问题;然后利用改进的粒子群算法对信任关系路径方案进行粒子映射,并通过对粒子粒距聚集度和粒子信息熵进行计算而修正粒子权值,再对粒子局部最优解和全局最优解进行更新;最后迭代的对信任关系路径解空间中的最优解进行搜索,并对最优路径的节点进行推荐信任度加权。仿真结果表明,改进算法具有较好的收敛速度和较强的有效性,且当节点跳级数较少时,可使系统数据信息估算获得最优的系统信任度。
[Abstract]:In order to solve the error of system data information caused by frequent withdrawal and addition of nodes in P2P network system, and aiming at the problems of high dependence of data acquisition on central node and incomplete acquisition of data information of nodes in system, an iterative optimization P2P network trust model based on evolutionary algorithm is proposed. Firstly, the system trust estimation model obtained by node data information in P2P network system is transformed into the path optimization problem of optimal trust relationship from source node to target node, then the improved particle swarm optimization algorithm is used to map the trust relationship path scheme, and the particle weight is modified by calculating the particle distance aggregation degree and particle information entropy, and then the local optimal solution and global optimal solution of particles are updated. Finally, the optimal solution in the solution space of trust relationship path is searched iteratively, and the recommended trust degree of the node of the optimal path is weighted. The simulation results show that the improved algorithm has good convergence speed and strong effectiveness, and when the number of node hops is small, the system data information estimation can obtain the optimal system trust.
【作者单位】： 山西大学;南京理工大学;
【分类号】：TP393.02
[Abstract]:In order to solve the error of system data information caused by frequent withdrawal and addition of nodes in P2P network system, and aiming at the problems of high dependence of data acquisition on central node and incomplete acquisition of data information of nodes in system, an iterative optimization P2P network trust model based on evolutionary algorithm is proposed. Firstly, the system trust estimation model obtained by node data information in P2P network system is transformed into the path optimization problem of optimal trust relationship from source node to target node, then the improved particle swarm optimization algorithm is used to map the trust relationship path scheme, and the particle weight is modified by calculating the particle distance aggregation degree and particle information entropy, and then the local optimal solution and global optimal solution of particles are updated. Finally, the optimal solution in the solution space of trust relationship path is searched iteratively, and the recommended trust degree of the node of the optimal path is weighted. The simulation results show that the improved algorithm has good convergence speed and strong effectiveness, and when the number of node hops is small, the system data information estimation can obtain the optimal system trust.
【作者单位】： 山西大学;南京理工大学;
【分类号】：TP393.02
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