【摘要】 分层分簇的无线传感器网络中,汇聚层节点的部署对于整个网络的性能是至关重要的。本文针对非均匀环境下,分层分簇无线传感器网络中汇聚层节点的优化部署进行研究,目标是以最少的节点和最低的总功率实现对感知层节点的全覆盖。这是一个典型的多目标优化问题。为此,提出了一种基于第二代快速非支配遗传算法(Non-dominated sorting genetic algorithm,NSGA-Ⅱ)的优化方案,以感知层节点全覆盖为前提,对汇聚层节点的数量和总功率进行联合优化。仿真结果表明,与常规均匀分布无线传感器的模型对比,本文所提出的部署方案能够在保证感知层节点全覆盖的前提下,显著减少汇聚层节点的数量,并降低了汇聚层节点的总功率,从而降低了部署成本,提高能量利用效率。更多还原

【Abstract】 In hierarchical clustering wireless sensor networks(WSNs),the deployment of convergence layer nodes is of great significance to the performance of the whole network. This paper investigates the optimal deployment of convergence layer nodes in hierarchical clustering WSNs in non-uniform scenarios. The objective is to achieve the full coverage of nodes in the sensing layer with the least nodes and the lowest total power in the convergence layer. This is a typical multi-objective optimization problem. In view of this,this paper proposes an optimization scheme based on the non-dominated sorting genetic algorithm II(NSGA-Ⅱ),which jointly optimizes the number and total power of convergence layer nodes on the premise of full coverage of sensing layer nodes. The simulation results show that the proposed deployment scheme can significantly reduce the number of convergence layer nodes and the total power of convergence layer nodes,thus reducing the deployment cost and improving the energy utilization efficiency,on the premise of ensuring the full coverage of sensing layer nodes.更多还原