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A Novel Framework of Multi-Hop Wireless Charging for Sensor Networks Using Resonant Repeaters

机译:使用谐振中继器的传感器网络多跳无线充电的新型框架

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Wireless charging has provided a convenient alternative to renew nodes’ energy in wireless sensor networks. Due to physical limitations, previous works have only considered recharging a single node at a time, which has limited efficiency and scalability. Recent advances on multi-hop wireless charging is gaining momentum and provides fundamental support to address this problem. However, existing single-node charging designs do not consider and cannot take advantage of such opportunities. In this paper, we propose a new framework to enable multi-hop wireless charging using resonant repeaters. First, we present a realistic model that accounts for detailed physical factors to calculate charging efficiencies. Second, to achieve balance between energy efficiency and data latency, we propose a hybrid data gathering strategy that combines static and mobile data gathering to overcome their respective drawbacks and provide theoretical analysis. Then, we formulate multi-hop recharge schedule into a bi-objective NP-hard optimization problem. We propose a two-step approximation algorithm that first finds the minimum charging cost and then calculates the charging vehicles’ moving costs with bounded approximation ratios. Finally, upon discovering more room to reduce the total system cost, we develop a post-optimization algorithm that iteratively adds more stopping locations for charging vehicles to further improve the results while ensuring none of the nodes will deplete battery energy. Our extensive simulations show that the proposed algorithms can handle dynamic energy demands effectively, and can cover at least three times of nodes and reduce service interruption time by an order of magnitude compared to the single-node charging scheme.
机译:无线充电为更新无线传感器网络中节点的能量提供了一种方便的替代方法。由于物理限制,以前的工作仅考虑一次为单个节点充电,这限制了效率和可伸缩性。多跳无线充电的最新进展势头强劲,并为解决该问题提供了基本支持。但是,现有的单节点充电设计没有考虑并且不能利用这种机会。在本文中,我们提出了一个新的框架,以使用谐振中继器实现多跳无线充电。首先,我们提出了一个现实的模型,该模型考虑了详细的物理因素以计算充电效率。其次,为了在能源效率和数据延迟之间取得平衡,我们提出了一种混合数据收集策略,该策略结合了静态和移动数据收集来克服它们各自的缺点并提供理论分析。然后,我们将多跳补给时间表制定为一个双目标NP硬性优化问题。我们提出了一种两步逼近算法,该算法首先找到最低充电成本,然后以有界的逼近比计算充电车辆的行驶成本。最后,在发现更多空间以降低总系统成本后,我们开发了一种后优化算法,该算法可反复添加更多的停车位置来为车辆充电,以进一步改善结果,同时确保所有节点都不会耗尽电池能量。我们广泛的仿真表明,与单节点计费方案相比,所提出的算法可以有效地处理动态能量需求,并且可以覆盖至少三倍的节点,并且将服务中断时间减少一个数量级。

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