基于种群阈值优化机制的WSN均衡覆盖算法

WSN Balanced Coverage Algorithm Based on Population ThresholdOptimization Mechanism

为解决无线传感网节点部署过程中存在的网络覆盖性能较差、离散节点数量不高等问题,提出了一种基于种群阈值优化机制的WSN均衡覆盖算法。采取定位机制,将传感节点视作可移位的动态粒子,设计了基于种群周期更新机制的定位覆盖方法,以提高节点布撒精度及均衡性。根据粒子的坐标偏移构建迭代裁决函数,将覆盖度较高的节点进行坐标偏移处理,以提高传感节点对区域的感知能力,从而增强网络的覆盖效果。同时,结合簇内最低覆盖距离等参数,设计了基于阈值优化机制的节点均衡方法,利用交叉判定阈值对节点坐标偏移进行校正处理。通过移动节点位置,对簇内区域进行再覆盖,以降低节点频繁移动而导致的能量受限现象,提升节点分布的离散程度,使覆盖均衡效果更佳。仿真实验结果显示,与当前无线传感网覆盖领域内常用的两种算法相比,此次所提出的算法网络区域覆盖能力更高、节点离散性能更强。

In order to solve the problems of poor network coverage performance and low number of discrete nodes in WSN node deployment,a WSN balanced coverage algorithm based on population threshold optimization mechanism is proposed.Firstly,the localization mechanism is adopted,and the sensor node is regarded as a dynamic particle which can be shifted.A localization and coverage method based on the population periodic update mechanism is designed to improve the node distribution accuracy and balance.According to the particle coordinate offset,an iterative decision function is constructed,and the nodes with higher coverage are processed by coordinate offset,so as to improve the sensing ability of sensor nodes to the region,thus increasing the efficiency of network coverage effect.Then,combined with the minimum coverage distance and other parameters in the cluster,a node balancing method based on the threshold optimization mechanism is designed.The node coordinate offset is corrected by using the cross judgment threshold,and the area in the cluster is covered again by moving the node position,which reduces the energy limitation caused by the frequent movement of nodes and improves the dispersion degree of node distribution to better the effect of coverage equalization.Simulation results show that,compared with the two algorithms commonly used in wireless sensor network coverage field,the proposed algorithm has higher network area coverage ability and stronger node dispersion performance.