基于改进粒子群算法的制造车间WSN部署优化

Node Deployments Optimization in Wireless Sensor Networks Based on Improved Particle Swarm Algorithm

针对制造车间环境下有向无线传感器网络节点的部署优化问题,以提高网络覆盖率为目标,提出了一种面向制造车间应用的有向感知模型,并设计了一种改进粒子群算法,改进算法惯性权重余弦自适应调整,同时学习因子基于惯性权重自行调节,并应用于有向感知模型求解优化,通过实验对比验证,设计算法具有较快的收敛速度以及全局寻优能力,有效提升了无线传感器网络覆盖率。

Aming at the node deployments in Wireless Sensor Networks under the manufacturing environment,with the goal of improving coverage of Wireless Sensor Networks,a directional sensing mode for the manufacturing was proposed and a improved particle swarm optimization algorithm using for model optimization was designed,the inertia weight of improved algorithm can be self-adaptive based on the cosine,and the learning factors was self-adaptive based on the inertia weight.The proposed algorithm is proved to be effective by comparative experiments and enhanced the coverage of wireless sensor networks effectively.