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A Novel Coverage Enhancing Algorithm for Hybrid Wireless Sensor Networks

机译:混合无线传感器网络的新型覆盖增强算法

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摘要

Providing field coverage is a key task in many sensor network applications. In some applications, the sensor field may have coverage holes due to random initial deployment of sensors and thus the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem by repositioning a portion of the mobile sensors to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a novel coverage-enhancing algorithm for hybrid wireless sensor networks. It consists of two phases. In the first phase, we use a genetic algorithm to compute the candidate target positions of the mobile sensor nodes. In the second phase, we use an optimization scheme on the candidate target positions resulted from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage-distance rate and the number of moved mobile sensors than the GA, the PSO algorithm, and the virtual force algorithm.
机译:在许多传感器网络应用中,提供现场覆盖是一项关键任务。在一些应用中,由于传感器的随机初始部署,传感器区域可能具有覆盖孔,因此无法实现所需的覆盖水平。通过重新放置一部分移动传感器以满足网络覆盖要求,混合无线传感器网络是解决此问题的一种经济高效的解决方案。本文研究如何在混合无线传感器网络中重新部署移动传感器节点以提高网络覆盖率。我们为混合无线传感器网络提出了一种新颖的覆盖增强算法。它包括两个阶段。在第一阶段,我们使用遗传算法来计算移动传感器节点的候选目标位置。在第二阶段,我们对第一阶段产生的候选目标位置使用优化方案,以减少移动传感器的累积潜在移动距离,从而可以精确移动需要移动的传感器节点及其最终目标位置被确定。实验结果表明,与遗传算法,粒子群优化算法和虚拟力算法相比,该算法在区域覆盖率,平均移动距离,区域覆盖距离率和移动传感器的数量方面有了明显的提高。

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