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A hybrid framework combining solar energy harvesting and wireless charging for wireless sensor networks

机译:将太阳能收集和无线充电相结合的混合框架,用于无线传感器网络

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Recently, there have been a growing number of applications that power wireless sensor networks (WSNs) by wireless charging technology. Although previous studies indicate that wireless charging can deliver energy reliably, it still faces regulatory challenges to provide high power density without incurring health risks. In particular, in clustered WSNs there exists a mismatch between the high energy demands from cluster heads and the relatively low energy supplies that wireless charging can provide. Fortunately, solar energy harvesting can provide high power density which is also risk-free. However, it is subject to weather dynamics. Therefore, in this paper, we propose a hybrid framework that combines the two technologies - cluster heads are equipped with solar panels to scavenge solar energy and the rest of nodes are powered by wireless charging. First, we study a placement problem on how to deploy solar-powered cluster heads that can minimize overall cost and propose a distributed 1.61(1 + ϵ)2-approximation algorithm for the placement. Second, we establish an energy balance in the network and explore how to maintain such balance when sunlight is unavailable. Third, we consider combining wireless charging and mobile data gathering in a joint tour in such networks, and propose a polynomial-time scheduling algorithm. Our extensive simulation demonstrates that the hybrid framework can reduce battery depletion by 20% and save system cost by 25% compared to previous results.
机译:近年来,越来越多的应用程序通过无线充电技术为无线传感器网络(WSN)供电。尽管以前的研究表明无线充电可以可靠地提供能量,但是在提供高功率密度而不带来健康风险的前提下,无线充电仍然面临监管挑战。特别是,在群集的WSN中,来自群集头的高能量需求与无线充电可以提供的相对较低的能量供应之间不匹配。幸运的是,太阳能收集可以提供高功率密度,这也是无风险的。但是,它受天气动态的影响。因此,在本文中,我们提出了一种将两种技术结合在一起的混合框架-簇头配备了太阳能电池板以清除太阳能,其余节点则通过无线充电供电。首先,我们研究了如何部署太阳能簇头以最大程度降低总成本的布置问题,并提出了一种用于布置的分布式1.61(1 + ϵ)2-近似算法。其次,我们在网络中建立能量平衡,并探索在没有阳光时如何保持这种平衡。第三,我们考虑在此类网络的联合巡回中结合无线充电和移动数据收集,并提出多项式时间调度算法。我们广泛的仿真表明,与以前的结果相比,混合动力框架可将电池耗电量减少20%,并将系统成本节省25%。

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