基于二进制差分算法的HWSN目标覆盖研究

本文对三维空间异构传感器网络的概率感知模型进行研究，为解决用最少工作节点覆盖区域内所有目标这一问题，将二进制差分算法融入到目标覆盖算法中．仿真实验表明，在覆盖所有目标前提下，二进制差分算法与遗传算法相比，所需工作传感器个数和迭代次数均有减少，证明了二进制差分算法可以有效解决该问题．与此同时探讨了感知半径，目标密集度和衰减因子等因素对于覆盖问题的影响．

Research of target coverage in HWSN based on binary differential evolution algorithm

The probability perception model of three dimensional space heterogeneous sensor network was re- searched. In order to solve the problem of covering all the goals in the region with the least number of nodes, the bi- nary difference algorithm is merged into the target coverage algorithm. Simulation results show that, compared to the binary difference algorithm and genetic algorithm, in the premise of covering all targets, both the number of sensors and iterations declined, proving that the binary differential evolution method can solve this problem effectively. And this paper also explored the impacts of perception radius, target density and attenuation factor, etc. on the coverage.