基于参数可变遗传算法的炮兵通信网络覆盖控制优化

Optimal Coverage Strategy Based on Alterable Parameter Genetic Algorithm in Artillery Commutation Networks

针对节点高密度部署的炮兵通信网络中优化工作节点集的选取问题,提出一种基于参数可变遗传算法的覆盖控制优化方法。设计了密度检测机制优化初始种群,并设计了即考虑到进化代数对算法影响,又考虑到每代中不同个体适应度对算法作用的自适应交叉概率和变异概率。仿真实验及分析表明,该优化方法快速有效地实现了工作节点数目少、节点集覆盖率高的工作节点集的选取,可有效地降低能耗,延长网络生存时间。

An optimal coverage strategy based on adaptive genetic algorithm in wireless sensor networks is proposed for solving the problem of selecting the optimal coverage set of nodes for artillery commutation networks with high density nodes.The mechanism of density detection is designed to optimize the initial population.The adaptive crossover probability and adaptive mutation probability are proposed,which consider the influence of every generation to algorithm and the effect individual fitness in every generation.Simulation and analysis results show that the optimal coverage set of nodes with less nodes and high coverage percentage is achieved by the proposed algorithm.Under the condition,sleeping chance is ensured adequately,which decreases the energy expenditure effectively and prolongs the lifetime of the network.