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Charging Route Planning for Wireless Rechargeable Sensor Networks

机译:无线可充电传感器网络的充电路线规划

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As an essential part of IoTs, wireless sensor networks are inseparable from its future development. However, sensor nodes are usually deployed in some complex and harsh areas, and it is difficult to replacing batteries manually. Thus, energy is the most key factor affecting the life cycle of wireless sensor networks. The energy loss occurs during the process of recharging and the movement among the sensors. To maintain the normal operation of the networks, sensors need to be recharged by deploying chargers. Therefore, we aim to find the shortest route. This paper studies two optimal routes planning of chargers by developing models based on genetic algorithm. The first route planning is in the case of only one mobile charger in the network. The second is based on the network with four chargers. After performing millions of iterations, the optimal dispatching scheme of mobile chargers was obtained.
机译:作为IOT的重要组成部分,无线传感器网络与未来的开发密不可分。 但是,传感器节点通常部署在一些复杂和严苛的区域中,并且难以手动更换电池。 因此,能量是影响无线传感器网络生命周期的最关键因素。 在再充电和传感器之间的运动过程中发生能量损失。 为了维持网络的正常运行,需要通过部署充电器来充电传感器。 因此,我们的目标是找到最短的路线。 本文通过基于遗传算法开发模型研究了充电器的两个最佳路线规划。 第一路线规划是网络中只有一个移动充电器的情况。 第二个是基于具有四个充电器的网络。 在执行数百万次迭代之后,获得了移动充电器的最佳调度方案。

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