本文研究了无线传感网络节点能效性测量优化问题。给出了无线传感网络分簇式拓扑结构和节点概率检测模型,建立了网络测量覆盖率指标和通信能耗指标。遗传算法和微粒群算法在节点能效性测量优化时存在容易陷入局部最优和精度不高的缺点。将禁忌搜索算法和遗传算法结合,增强了遗传算法的全局搜索能力。仿真实验证明,采用遗传-禁忌搜索算法进行节点能效性测量优化时,网络测量覆盖率更高,通信能耗更小,优化效果更好。
This paper researches the problem of energy efficient optimization for the measurement of wireless sensor nodes. Based on the cluster-based topology and probability sensing model, the metric of network measurement coverage and communicate energy consumption are established. Genetic algorithm is easy to stuck in local optimum; particle swarm optimization can't get a high precise result. Combining genetic algorithm and tabu search algorithm can improve the performance of genetic algorithm. The simulation experiments show that comparing to genetic algorithm, the network measurement coverage is getting higher and the communicate energy consumption is getting lower when using the GA-TS algorithm.