利用共振中继器提高无线可充电传感器网络的充电能力

Cong Wang, Ji Li, Fan Ye, Yuanyuan Yang
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引用次数: 29

摘要

无线充电为无线传感器网络中传感器的能量更新提供了一种方便的替代方案。由于物理限制,以往的工作只考虑一次给单个节点充电,效率和可扩展性有限。近年来,多跳无线充电技术的发展势头日益强劲,为解决这一问题提供了基础支持。然而,现有的单节点充电设计没有考虑到也无法利用这样的机会。在本文中,我们提出了一个新的框架,使多跳无线充电使用谐振中继器。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来计算充电效率。其次,为了在能源效率和数据延迟之间取得平衡,我们提出了一种将静态和移动数据采集相结合的混合数据采集策略,以克服各自的缺点,并进行了理论分析。然后将多跳充值计划转化为一个双目标NP-hard优化问题。提出了一种两步逼近算法,首先求出最小充电成本,然后用有界逼近比计算充电车辆的移动成本。最后,在发现更多降低系统总成本的空间后,我们开发了一种后优化算法,迭代地增加充电车辆的停车位置,以进一步改善结果。大量的仿真结果表明,与单节点充电方案相比,该算法可以有效地处理动态能源需求,并且可以覆盖至少三个节点,并将服务中断时间减少一个数量级。
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Improve Charging Capability for Wireless Rechargeable Sensor Networks Using Resonant Repeaters
Wireless charging has provided a convenient alternative to renew sensors' 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 advance on multi-hop wireless charging is gaining momentum to provide 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. 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.
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