Multi-objective evolutionary algorithm based on decomposition for efficient coverage control in mobile sensor networks

B. Attea, F. Y. Okay, S. Ozdemir, M. Akcayol
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引用次数: 12

Abstract

Node deployment is a fundamental issue to be solved in Wireless Sensor Networks (WSNs). A proper node deployment scheme can reduce the complexity of problems in WSNs such as routing, data fusion, communication, etc. Furthermore, it can extend the lifetime of WSNs by minimizing energy consumption due to sensing and communication. This paper presents the development of a recently multi-objective optimization algorithm, the so-called multi-objective evolutionary algorithm based on decomposition (MOEA/D). MOEA/D aims the relocation of mobile nodes in a WSN with the goal of providing maximum sensing coverage area, and with the constraint of minimizing the energy required for the relocation as measured by total travel distance of the sensors from their initial locations to their final locations. Simulation results clearly show that the non-dominated solutions have tradeoff between the travelled distance and coverage area.
基于分解的多目标进化算法在移动传感器网络中的有效覆盖控制
节点部署是无线传感器网络中需要解决的一个基本问题。合理的节点部署方案可以降低无线传感器网络中路由、数据融合、通信等问题的复杂性。此外,它可以通过最小化由于传感和通信造成的能量消耗来延长无线传感器网络的使用寿命。本文介绍了一种新的多目标优化算法,即基于分解的多目标进化算法(MOEA/D)。MOEA/D的目标是在WSN中移动节点的重新定位,以提供最大的传感覆盖区域为目标,并以传感器从初始位置到最终位置的总行程距离来衡量重新定位所需的能量最小化为约束。仿真结果清楚地表明,非支配解在移动距离和覆盖面积之间进行了权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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