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Two-phase node deployment for target coverage in rechargeable WSNs using genetic algorithm and integer linear programming

机译:使用遗传算法和整数线性规划可充电WSN中目标覆盖的两相节点部署

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Node deployment is a matter of considerable concern in designing wireless sensor networks (WSNs). This paper studies this issue in the context of rechargeable WSNs (RWSNs). We propose an efficient algorithm, namely node deployment for target coverage in RWSNs (NDTCR), which determines the number and positions of installed sensors in two phases. The first phase applies genetic algorithm to construct a mesh over a subset of positions. The mentioned mesh covers the targets and connects them to the sink. In the second phase of NDTCR, we propose an integer linear programming (ILP) model to install some sensors at each position of the mesh. The advantage of applying the first phase is that it prunes the solution space considerably. Therefore, the proposed ILP model can be solved in a reasonable time. The experimental results demonstrate that NDTCR requires 29% fewer sensors on average in comparison with the previous approaches.
机译:节点部署是设计无线传感器网络(WSNS)的相当关注的问题。本文在充电WSN(RWSN)的背景下研究了这个问题。我们提出了一种有效的算法,即RWSN(NDTCR)中的目标覆盖的节点部署,其在两个阶段中确定已安装的传感器的数量和位置。第一阶段应用遗传算法在位置子集上构造网格。所提到的网格覆盖了目标并将它们连接到水槽。在NDTCR的第二阶段,我们提出了一个整数线性编程(ILP)模型,用于在网格的每个位置安装一些传感器。施加第一阶段的优点是它显着提出了解决方案空间。因此,所提出的ILP模型可以在合理的时间内解决。实验结果表明,与先前的方法相比,NDTCR平均需要29%的传感器。

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