基于改进遗传算法的无线传感网覆盖优化

Coverage Optimization of Hybrid Wireless Sensor Network Based on Improved Genetic Algorithm

摘要:

为提高混合无线传感器网络(WSNs)的覆盖率,将改进的遗传算法应用到WSNs覆盖优化中,通过合理调整移动节点的位置来提高网络覆盖率;针对传统群体智能算法易“早熟”,最大迭代次数需试探设定等缺陷,提出了基于多个种群并行优化的改进遗传算法;多个种群之间并不独立,而是通过移民算子相互联系；分别利用人工选择算子与精华种群选择并记录各个种群每一代最优染色体；并利用精华种群中保存的最优染色体设计出新的进化终止条件;仿真结果表明,改进的遗传算法不仅无需设定最大迭代次数而且收敛速度快,更兼有效地提高了WSNs的覆盖率。

Abstract:

In order to improve the coverage performance,an improved genetic algorithm was applied to coverage optimization of hybrid wireless sensor networks (WSNs).Coverage performance can be improved by changing location of mobile nodes. Traditional intelligence algorithm is liable to fall into the trap of premature and its largest number of iterations is difficult to determine. An improved genetic algorithm is proposed to fill the gaps. Multiple populations can be connected with others by immigration operator. Optimal individual of each population in every generation can be selected by artificial selection operator and recorded by essence of population. A new stopping criterion for iteration is presented according to the recorded information. Simulation shows that our improved genetic algorithm needn't set maximum number of iterations ,has fast convergence rate, and effectively improves coverage performance of WSNs.