基于多策略改进麻雀搜索算法的WSN覆盖优化

WSN Coverage Optimization Based on Multi-Strategy Improved Sparrow Search Algorithm

为了解决无线传感器网络节点分布不均匀、无线传感器网络覆盖率不高的问题,本文通过采用多策略改进麻雀搜索算法(DSSA)实现网络覆盖优化。利用Delaunay三角划分策略在目标区域构建三角网络,以此部署静态节点;其次引入了惯性权重余弦动态调整策略和步长速度自适应调整策略完成对网络节点的二次部署,提高算法全局搜索能力。仿真实验表明DSSA算法可以有效提高覆盖率,避免陷入局部最优,覆盖率比其他4种算法分别提高了4.31%、6.26%、3.16%、13.21%,结果验证了DSSA算法在无线传感器网络覆盖方面具有可行性与优越性。

In order to solve the problem of uneven distribution of wireless sensor network nodes and low coverage of wireless sensor network,this paper achieved network coverage optimization by using the multi-strategy improved sparrow search algorithm(DSSA).The Delaunay triangular division strategy was utilized to construct a triangular network in the target area,so as to deploy the static nodes.Secondly,the inertia weight cosine dynamic adjustment strategy and the step speed adaptive adjustment strategy were introduced to complete the secondary deployment of the network nodes,and improve the algorithm's global search capability.Simulation experiments showed that the DSSA algorithm could effectively improve the coverage rate,and avoid falling into the local optimum,the coverage rate than the other four algorithms were increased by 4.31%,6.26%,3.16%,13.21%,respectively.The results verified that the DSSA algorithm had the feasibility and superiority in the wireless sensor network coverage.