基于改进粒子群的无线传感网络覆盖优化方法

Coverage Optimization of Wireless Sensor Networks Based on Improved Particle Swarm Optimization

常规的无线传感网络覆盖方法一般采用三角划分策略,存在覆盖节点分布不均匀、覆盖范围有限、覆盖率较低等不足,具有较大的局限性。针对此问题,引入改进粒子群算法,提出一种全新的覆盖优化方法。首先,设计无线传感网络区域覆盖,使传感器节点均匀覆盖在整个待监测物体所在区域;其次,建立节点感知模型,实时反映像素点与无线传感器节点距离的动态变化;最后,设计基于改进粒子群的覆盖优化算法,实现无线传感网络覆盖率最大化的目标。实验结果表明,所提方法能够显著提高网络区域覆盖率,覆盖率均在96%以上,全局覆盖优化能力较强。

The conventional coverage methods of wireless sensor networks generally adopt triangulation strategy,which has some disadvantages such as uneven distribution of coverage nodes,limited coverage,low coverage,and so on,and has great limitations.To solve this problem,an improved particle swarm optimization algorithm is introduced and a new coverage optimization method is proposed.Firstly,the wireless sensor network area coverage is designed to make the sensor nodes uniformly cover the whole area of the object to be monitored.Secondly,a node sensing model is established to reflect the dynamic change of the distance between the pixel and the wireless sensor node in real time.Finally,a coverage optimization algorithm based on improved particle swarm optimization is designed to achieve the goal of maximizing the coverage of wireless sensor networks.The experimental results show that the proposed method can significantly improve the regional coverage of the network,and the coverage is above 96%.The global coverage optimization ability is strong.