实时环境下无线传感器网络覆盖最大化的多目标优化方法

N. Meena, Buddha Singh
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引用次数: 3

摘要

无线传感器网络设计中最重要的服务质量问题是网络连通性和感知覆盖。目标区域被传感器监测或跟踪,称为覆盖范围。在恶劣的环境中,人类很难或不可能介入,那么传感器就会被飞机扔下。在这种情况下,传感器不可能在整个区域内都是相同的,因此有些区域可能被覆盖或未被覆盖,有些传感器可能重叠。这些冗余传感器提高了覆盖范围和连通性,但增加了能源消耗。由于覆盖孔对无线传感器网络的危害和否定作用,对其进行监测是一项重要的任务。在本文中,我们提出了一种利用多目标优化方法来延长网络寿命和最大覆盖率的模型。该模型可以实现最大的覆盖范围、最小的能耗和最大的网络寿命。本文考虑非支配排序遗传算法(NSGA-II)来优化覆盖问题。仿真结果表明,该方法在提高网络覆盖概率和生存期的同时,能够保持网络的连通性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coverage Maximization using Multi-Objective Optimization Approach for Wireless Sensor Network in Real Time Environment
The most important issue of Quality of Service is network connectivity and coverage of sensing in the design of Wireless Sensor Network. The target area is monitoring or tracking by the sensors, called as coverage. Where the human intrusion is difficult or impossible in a hostile environment then the sensors are dropped by airplanes. In this situation sensors cannot be same in the whole area, therefore some area may be covered or uncovered and some sensors may be overlapped. These redundant sensors improve coverage and connectivity, but increase energy depletion. Monitoring of the coverage holes is an important task because of their harmful and denying effect on the WSNs. In the present paper, we have proposed a model to extend the network lifetime and maximum coverage rate using multi-objective optimization approach. This model can achieve maximum coverage, minimum energy consumption and maximize network lifetime. This paper considers non-dominated sorting genetic algorithm (NSGA-II) for optimizing coverage problems. The results of the simulation show that the proposed method can improve the coverage probability and lifetime of the network at the same time can maintain the connectivity of the network.
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