4.8 Article

Energy-Efficient Mobile Charging for Wireless Power Transfer in Internet of Things Networks

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 5, Issue 1, Pages 79-92

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2017.2772318

Keywords

Internet of Things (IoT); mobile charging; wireless charging; wireless power transfer

Funding

  1. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Science and ICT [NRF-2017R1A2B4009802]
  2. Chung-Ang University Graduate Research Scholarship
  3. National Research Foundation of Korea [2017R1A2B4009802] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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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.

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