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Coverage Maximization using Multi-Objective Optimization Approach for Wireless Sensor Network in Real Time Environment

机译:实时环境中使用多目标优化方法的无线传感器网络覆盖最大化

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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.
机译:服务质量最重要的问题是无线传感器网络设计中的网络连接性和传感范围。目标区域由传感器监视或跟踪,称为覆盖范围。在敌对环境中难以或不可能进行人为入侵的地方,传感器会被飞机掉落。在这种情况下,传感器不能在整个区域中都相同,因此某些区域可能会被覆盖或未覆盖,而某些传感器可能会重叠。这些冗余传感器改善了覆盖范围和连通性,但增加了能量消耗。监视覆盖漏洞是一项重要任务,因为它们会对WSN产生有害和负面影响。在本文中,我们提出了一种使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,最低的能耗并最大程度地延长网络寿命。本文考虑了非优势排序遗传算法(NSGA-II)来优化覆盖问题。仿真结果表明,所提方法可以提高网络的覆盖概率和寿命,同时可以保持网络的连通性。

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