International Journal of Internet, Broadcasting and Communication

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Energy-efficient charging of sensors for UAV-aided wireless sensor network

  • Rahman, Shakila (Department of Electrical, Electronic, and Computer Engineering, University of Ulsan) ;
  • Akter, Shathee (Department of Electrical, Electronic, and Computer Engineering, University of Ulsan) ;
  • Yoon, Seokhoon (Department of Electrical, Electronic, and Computer Engineering, University of Ulsan)
  • Received : 2022.09.05
  • Accepted : 2022.09.11
  • Published : 2022.11.30
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Abstract

Lack of sufficient battery capacity is one of the most important challenges impeding the development of wireless sensor networks (WSNs). Recent innovations in the areas of wireless energy transfer and rechargeable batteries have made it possible to advance WSNs. Therefore, in this article, we propose an energy-efficient charging of sensors in a WSN scenario. First, we have formulated the problem as an integer linear programming (ILP) problem. Then a utility function-based greedy algorithm named UGreedy/UF1 is proposed for solving the problem. Finally, the performance of UGreedy/UF1 is analyzed along with other baseline algorithms: UGreedy/UF2, 2-opt TSP, and Greedy TSP. The simulation results show that UGreedy/UF1 performs better than others both in terms of the deadline missing ratio of sensors and the total energy consumption of UAVs.

Keywords

Acknowledgement

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) by the Ministry of Education under Grant 2021R1I1A3051364.

References

  1. Su, Chunxia, et al., "UAV-assisted wireless charging for energy-constrained IoT devices using dynamic matching", The Journal of The Institute of Internet, IEEE Internet of Things Journal, Vol. 7, Issue. 6, June 2020. DOI: https://doi.org/ 10.1109/JIOT.2020.2968346
  2. Li, Songyang, et al., "Improving charging performance for wireless rechargeable sensor networks based on charging uavs: a joint optimization approach", 2020 IEEE Symposium on Computers and Communications (ISCC), pp. 1-7, July 07-10, 2020. DOI: https://doi.org/10.1109/ISCC50000.2020.9219670
  3. Basha, Elizabeth, et al., "UAV recharging opportunities and policies for sensor networks", International Journal of Distributed Sensor Networks, August 11, 2015. DOI: https://doi.org/ 10.1155/2015/824260
  4. Yang, Longan, et al, "An Efficient Charging Algorithm for UAV-aided Wireless Sensor Networks", 2020 IEEE 6th International Conference on Computer and Communications (ICCC), pp. 834-838, 2020. DOI: https://doi.org/10.1109/ICCC51575.2020.9345142
  5. Chen, Jingjing, Chang Wu Yu, and Wen Ouyang, "Efficient wireless charging pad deployment in wireless rechargeable sensor networks", IEEE Access, Vol. 8, pp. 39056-39077, 2020. DOI: https://doi.org/ 10.1109/ACCESS.2020.2975635
  6. Peng, Wei, and David J. Edwards, "K-means like minimum mean distance algorithm for wireless sensor networks", 2010 2nd International Conference on Computer Engineering and Technology, Vol. 1, 2010. DOI: https://doi.org/10.1109/ICCET.2010.5486264
  7. Wu, Pengfei, et al., "Trajectory Optimization for UAVs' Efficient Charging in Wireless Rechargeable Sensor Networks", IEEE Transactions on Vehicular Technology, Vol. 69, Issue. 4, pp. 4207-4220, 2020. DOI: https://doi.org/ 10.1109/TVT.2020.2969220
  8. Thibbotuwawa, Amila, et al., "Planning deliveries with UAV routing under weather forecast and energy consumption constraints", IFAC-PapersOnLine, Vol. 52, Issue. 13, pp. 820-825, 2019. DOI: https://doi.org/ 10.1016/j.ifacol.2019.11.231
  9. Jia, Jie, et al., "Joint power charging and routing in wireless rechargeable sensor networks", Sensors, Vol. 17, Issue. 10, 2017. DOI: https://doi.org/ 10.3390/s17102290
  10. Zhou, Yongquan, et al., "A discrete invasive weed optimization algorithm for solving traveling salesman problem", Neurocomputing, Vol. 151, pp. 1227-1236, March 2015. DOI: https://doi.org/ 10.1016/j.neucom.2014.01.078