一种改进粒子群迭代优化的集成网络智能节点部署算法

Integrated Network Intelligent Node Deployment Algorithm of Improved Particle Swarm Optimization Iteration

为了解决复杂环境中集成网络系统的智能节点交叉覆盖和相互干扰对智能节点最优位置选择的影响问题,提出了一种改进粒子群迭代优化的集成网络智能节点部署算法。在该算法中,首先将集成网络系统智能节点部署模型转化为在交叉率和干扰约束目标下的优化问题;然后利用改进粒子群算法对节点部署方案进行映射,依据粒子粒距聚类度和粒子信息熵对粒子权值进行修正,再计算粒子的适应度值,对粒子的局部最优解和全局最优解进行更新;最后利用粒子速度和位置更新策略对智能节点部署进行迭代优化。仿真对比实验证明,该算法具有较好的收敛速度,且收敛值更优,有效地保证了在覆盖率最大时干扰最小。

In order to solve effects of intelligent node cross cover and mutual interference in complex environment inte- grated network system on intelligent node optimal position select, an integrated network intelligent node deployment al- gorithm of improved particle swarm optimization iteration was proposed. This algorithm first integrates network system intelligent node deployment model into the cross rate and interference constraint targets optimization problems, then u- ses the improved particle swarm optimization （pso） algorithm to map node deployment scheme, on the basis of the par- ticle grain distance clustering degree and particle information entropy modifies particle weights, and then computes of the particle~ s fitness value, updates the local optimal solution and the global optimal solution of the particle, finally, u- ses the particle velocity and position update strategies to make iterative optimization to intelligent node deployment. Simulation experiments show that this algorithm has good convergence speed and convergence value is more excellent, effectively guarantees the maximum interference minimum coverage.