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A Novel Data Collection and Partial Charging Scheme Using Multiple Mobile Vehicles in Wireless Rechargeable Sensor Networks

  • Research Article-Computer Engineering and Computer Science
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Abstract

In wireless rechargeable sensor networks (WRSNs), due to data collection and charging, energy efficiency is a crucial factor because it affects the network’s reliability and performance. Wireless energy transfer (WET) and wireless data collection (WDC) using separate vehicles are two promising new methods for improving the energy efficiency of sensors. We combine WET and WDC on a single mobile vehicle (MV) to charge and collect data from the sensors by traversing specified sojourn locations within the WRSNs. The objective of this work is to maximize data collection per unit of energy and reduce the number of inactive sensors. In order to accomplish this, we propose a novel scheme, namely DCPCS, that includes two heuristics and two optimization algorithms. We utilized the circle-covering algorithm to determine sojourn locations based on energy consumption rates and the location of sensors. The ant lion optimization (ALO) algorithm partitions the network into the minimum number of regions, assigns a MV to each region, and ensures balanced total energy consumption among the MVs. The ALO algorithm utilizes the first heuristic algorithm to validate the regions for the MVs. Subsequently, the discrete grey wolf optimization algorithm determines the optimal order of the sojourn locations for data collection and charging by a MV within a region. To accomplish our objectives, we propose a heuristic data collection and partial charging strategy to determine the sojourn times of the MVs at the sojourn locations. We conduct simulations and compare the results of the proposed DCPCS scheme with three existing schemes. The simulation outcomes demonstrate that our proposed scheme outperforms the other schemes in terms of various performance metrics.

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In this work, the standard datasets are not used. The data generated and analyzed during the current study are available in the experiment section.

References

  1. Haseeb, K.; Ud Din, I.; Almogren, A.; Islam, N.: An energy efficient and secure IoT-based WSN framework: an application to smart agriculture. Sensors 20(7), 2081 (2020)

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  2. Akkaş, M.A.; Sokullu, R.; Çetin, H.E.: Healthcare and patient monitoring using IoT. Internet Things 11, 100173 (2020)

    Article  Google Scholar 

  3. Kadir, E.A.; Irie, H.; Rosa, S.L.: Modeling of wireless sensor networks for detection land and forest fire hotspot. In: 2019 International Conference on Electronics, Information, and Communication (ICEIC), pages 1–5. IEEE (2019).

  4. Jaigirdar, F.T.; Islam, M.M.: A new cost-effective approach for battlefield surveillance in wireless sensor networks. In: 2016 International Conference on Networking Systems and Security (NSysS), pp. 1–6. IEEE (2016).

  5. Lyu, Z.; Wei, Z.; Wang, X.; Fan, Y.; Xia, C.; Shi, L.: A periodic multinode charging and data collection scheme with optimal traveling path in WRSNs. IEEE Syst. J. 14(3), 3518–3529 (2020)

    Article  ADS  Google Scholar 

  6. Wei, Z.; Xia, C.; Yuan, X.; Sun, R.; Lyu, Z.; Shi, L.; Ji, J.: The path planning scheme for joint charging and data collection in WRSNs: a multi-objective optimization method. J. Netw. Comput. Appl. 156, 102565 (2020)

    Article  Google Scholar 

  7. Yadav, C.B.; Dash, D.: An energy efficient periodic data gathering and charging schedule using MVs in wireless rechargeable sensor networks. Computing 105, 2563–2593 (2023)

    Article  MathSciNet  Google Scholar 

  8. Liu, B.-H.; Nguyen, N.-T.; Pham, V.-T.; Lin, Y.-X.: Novel methods for energy charging and data collection in wireless rechargeable sensor networks. Int. J. Commun. Syst. 30(5), e3050 (2017)

    Article  Google Scholar 

  9. Boukerche, A.; Qiyue, W.; Sun, P.: A novel joint optimization method based on mobile data collection for wireless rechargeable sensor networks. IEEE Trans. Green Commun. Netw. 5(3), 1610–1622 (2021)

    Article  Google Scholar 

  10. Yadav, C.B.K.; Dash, D.: An efficient partial charging and data gathering strategy using multiple MVs in WRSNs. Available at SSRN (2022). https://doi.org/10.2139/ssrn.4280030

  11. Guo, S.; Wang, C.; Yang, Y.: Mobile data gathering with wireless energy replenishment in rechargeable sensor networks. In: 2013 Proceedings IEEE INFOCOM, pp. 1932–1940. IEEE, Turin (2013).

  12. Zhao, M.; Li, J.; Yang, Y.: A framework of joint mobile energy replenishment and data gathering in wireless rechargeable sensor networks. IEEE Trans. Mob. Comput. 13(12), 2689–2705 (2014)

    Article  Google Scholar 

  13. Han, G.; Yang, X.; Liu, L.; Zhang, W.: A joint energy replenishment and data collection algorithm in wireless rechargeable sensor networks. IEEE Internet Things J. 5(4), 2596–2604 (2018)

    Article  Google Scholar 

  14. Liu, K.; Peng, J.; He, L.; Pan, J.; Li, S.; Ling, M.; Huang, Z.: An active mobile charging and data collection scheme for clustered sensor networks. IEEE Trans. Veh. Technol. 68(5), 5100–5113 (2019)

    Article  Google Scholar 

  15. Chen, Y.; Jiao, W.; Wenrui, Yu.: The combined strategy of energy replenishment and data collection in heterogenous wireless rechargeable sensor networks. IEEE Syst. J. 17(3), 1–12 (2022)

    Google Scholar 

  16. Jiao, W.; Tian, M.; Yun, X.: A combining strategy of energy replenishment and data collection in wireless sensor networks. IEEE Sens. J. 22(7), 7411–7426 (2022)

    Article  ADS  Google Scholar 

  17. Baek, J.; Han, S.I.; Han, Y.: Optimal UAV route in wireless charging sensor networks. IEEE Internet Things J. 7(2), 1327–1335 (2020)

    Article  Google Scholar 

  18. Zhang, M.; Cai, W.: Data collecting and energy charging oriented mobile path design for rechargeable wireless sensor networks. J. Sens. (2022).

  19. Anwit, R.; Jana, P.K.; Tomar, A.: Sustainable and optimized data collection via mobile edge computing for disjoint wireless sensor networks. IEEE Trans. Sustain. Comput. 7(2), 471–484 (2021)

    Article  Google Scholar 

  20. He, S.; Chen, J.; Jiang, F.; Yau, D.K.Y.; Xing, G.; Sun, Y.: Energy provisioning in wireless rechargeable sensor networks. IEEE Trans. Mob. Comput. 12(10), 1931–1942 (2012)

  21. Mirjalili, S.: The ant lion optimizer. Adv. Eng. Softw. 83, 80–98 (2015)

    Article  Google Scholar 

  22. Mirjalili, S.; Mirjalili, S.M.; Lewis, A.: Grey wolf optimizer. Adv. Eng. Softw. 69, 46–61 (2014)

  23. Panwar, K.; Deep, K.: Discrete grey wolf optimizer for symmetric travelling salesman problem. Appl. Soft Comput. 105, 107298 (2021)

  24. Croes, G.A.: A method for solving traveling-salesman problems. Oper. Res. 6(6), 791–812 (1958)

  25. Davendra, D.; Metlicka, M.; Bialic-Davendra, M.: CUDA accelerated 2-OPT local search for the traveling salesman problem. In: Novel Trends in the Traveling Salesman Problem, IntechOpen (2020)

  26. Liu, T.; Wu, B.; Zhang, S.; Peng, J.; Xu, W.: An effective multi-node charging scheme for wireless rechargeable sensor networks. In: IEEE INFOCOM 2020-IEEE Conference on Computer Communications, pp. 2026–2035. IEEE, Toronto (2020)

  27. He, L.; Linghe Kong, Y.G.; Pan, J.; Zhu, T.: Evaluating the on-demand mobile charging in wireless sensor networks. IEEE Trans. Mob. Comput. 14(9), 1861–1875 (2014)

    Article  Google Scholar 

  28. Tomar, A.; Muduli, L.; Jana, P.K.: An efficient scheduling scheme for on-demand mobile charging in wireless rechargeable sensor networks. Pervasive Mob. Comput. 59, 101074 (2019)

    Article  Google Scholar 

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Acknowledgements

This work is supported by the Science and Engineering Research Board, a statutory body of the Department of Science and Technology (DST), Govt. of India [Grant number: CRG/2023/001572]. We also like to thank the anonymous reviewers for their valuable comments.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Patna, Patna, Bihar, 800005, India

    Chandra Bhushan Kumar Yadav & Dinesh Dash

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  1. Chandra Bhushan Kumar Yadav
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  2. Dinesh Dash
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CBKY contributed to the methodology, coding, and writing. DD was involved in writing—review and editing and formal analysis.

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Correspondence to Chandra Bhushan Kumar Yadav.

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The authors declare that there is no conflict of interests regarding the publication of this article. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Yadav, C.B.K., Dash, D. A Novel Data Collection and Partial Charging Scheme Using Multiple Mobile Vehicles in Wireless Rechargeable Sensor Networks. Arab J Sci Eng (2024). https://doi.org/10.1007/s13369-023-08687-8

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