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Novel Algorithms for Complete Targets Coverage in Energy Harvesting Wireless Sensor Networks

机译：能量收集无线传感器网络中用于完全目标覆盖的新型算法

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This paper addresses the problem of maximizing the network lifetime of rechargeable Wireless Sensor Networks (WSNs) whilst ensuring all targets are monitored continuously by at least one sensor node. The objective is to determine a group of sensor nodes, and their wake-up schedule such that within a time interval, one subset of nodes are active whilst others enter the sleep state to conserve energy as well as recharge their battery. We propose a Linear Programming (LP) based solution to determine the activation schedule of sensor nodes whilst affording them recharging opportunities and at the same time ensures complete target coverage. The results show our LP solution achieves more than twice the performance in terms of network lifetime as compared to similar algorithms developed for finite battery WSNs. However, it is computationally expensive. We therefore propose Maximum Utility Algorithm (MUA), a few orders of magnitude faster approach that achieves 3/4 of the network lifetime obtained by our LP solution.
机译：本文解决了使可充电无线传感器网络（WSN）的网络寿命最大化的问题，同时确保至少一个传感器节点连续监控所有目标。目的是确定一组传感器节点及其唤醒时间表，以便在一个时间间隔内，一个节点子集处于活动状态，而其他节点子进入睡眠状态以节省能量并为其电池充电。我们提出一种基于线性规划（LP）的解决方案，以确定传感器节点的激活时间表，同时为它们提供充电机会，同时确保完整的目标覆盖范围。结果表明，与为有限电池WSN开发的类似算法相比，我们的LP解决方案在网络寿命方面实现了两倍以上的性能。然而，这在计算上是昂贵的。因此，我们提出了最大效用算法（MUA），这是一种快几个数量级的方法，可以实现LP解决方案获得的网络寿命的3/4。

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