Energy-Efficient Mobile Charging for Wireless Power Transfer in Internet of Things Networks
Energy-Efficient Mobile Charging for Wireless Power Transfer in Internet of Things Networks
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DOI：
10.1109/jiot.2017.2772318
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发表时间：
2018-02-01
影响因子：
10.6
通讯作者：
Cho, Sungrae
中科院分区：
文献类型：
--
作者：
Na, Woongsoo;Park, Junho;Cho, Sungrae
物联网（IoT）有望在下一代移动的通信业务的建设中发挥重要作用，目前已应用于各种业务中。然而，耗电的电池大大限制了物联网设备的使用寿命。在各种寿命延长技术中，本文讨论了移动的充电，它使无线电力传输基于射频与移动的充电器（MC）。MC充当移动目标物联网网络，为电池供电的物联网设备提供能量。然而，具有能量受限电池的MC导致旅行时间的限制。本文通过确定MC的运动路径和有效的充电点来最小化物联网设备充电的能量消耗，并证明了该问题是NP-难的。提出了一种求解该问题的有效算法--最佳充电效率（BCE），并利用线性规划的对偶性保证了BCE算法的上界。此外，还提出了一种改进的BCE算法，称为分支次优效率算法，并引入了附加的搜索技术。最后，分析了所提算法、最优解与现有算法在性能上的差异，并得出结论：所提算法的性能接近最优，在计费效率和时延方面的差异率在1%以内。
The Internet of Things (IoT) is expected to play an important role in the construction of next generation mobile communication services, and is currently used in various services. However, the power-hungry battery significantly limits the lifetime of IoT devices. Among the various lifetime extension techniques, this paper discusses mobile charging, which enables wireless power transfer based on radio frequency with mobile chargers (MCs). MCs function as traveling target IoT networks that provide energy to battery-operated IoT devices. However, MCs with an energy-constrained battery result in limitation of travel-time. This paper formulates a problem to minimize energy consumption for charging IoT devices by determining the path of motion of an MC and efficient charging points, and proves that the problem is NP-hard. An efficient algorithm, named best charging efficiency (BCE), is proposed to solve the problem and the upper bound of the BCE algorithm is guaranteed using the duality of linear programming. In addition, an improved BCE algorithm called branching second best efficiency algorithm with additional searching techniques is introduced. Finally, this paper analyzes the difference in performance among the proposed algorithms, optimal solutions, and the existing algorithm and concludes that the performance of the proposed algorithm is near optimal, within 1% of difference ratio in terms of charging efficiency and delay.