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Efficient charging schedules in a rechargeable wireless sensor network with multiple chargers

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Abstract

In a wireless sensor network (WSN) when a node’s battery drains out it becomes a dead node. Due to the recent advancement of mobile power transfer technology, it is feasible to charge the nodes of WSN by single or multiple mobile chargers (MC) of finite capacity thereby extending the network lifetime. It introduces a new paradigm of WSN namely rechargeable wireless sensor networks (RWSN), where the energy of nodes lying below a predefined threshold value is replenished to full capacity by the MCs. The determination of an MC charging schedule resembles a constrained traveling salesman problem (TSP) which is NP-complete. So here we propose for RWSN with multiple MCs two recharging heuristics MEWLST_C and MEWLST_NC for clustered and non-clustered environments respectively based on the concept of the latest start time (lst) to charge a requesting node. A node is chargeable when an MC reaches before it dies out and charges it to full capacity. The MC should have sufficient energy to return to the base station (BS) after charging the node, a condition called MC’s reachability. Our proposals ensure an accepted request is chargeable and the corresponding MC satisfies the reachability criteria. Extensive simulation studies reveal that our method maximizes overall node survival ratio (\(\delta\)), while maintaining the almost same or moderately improved Moving Energy Ratio of the MCs (\(\gamma\)) compared with the recent state of the art.

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References

  1. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Netw 38(4):393–422

    Article  Google Scholar 

  2. Kuila P, Jana PK (2014) Energy efficient clustering and routing algorithms for wireless sensor networks: particle swarm optimization approach. Eng Appl Artif Intell 33:127–140

    Article  Google Scholar 

  3. Rajagopalan R, Varshney PK (2006) Data aggregation techniques in sensor networks: a survey

  4. Demirkol I, Ersoy C, Alagoz F (2006) Mac protocols for wireless sensor networks: a survey. IEEE Commun Mag 44(4):115–121

    Article  Google Scholar 

  5. Di Francesco M, Das SK, Anastasi G (2011) Data collection in wireless sensor networks with mobile elements: a survey. ACM Trans Sens Netw (TOSN) 8(1):1–31

    Article  Google Scholar 

  6. Sah DK, Amgoth T (2020) Renewable energy harvesting schemes in wireless sensor networks: a survey. Inf Fusion 63:223–247

    Article  Google Scholar 

  7. Kurs A, Karalis A, Moffatt R, Joannopoulos JD, Fisher P, Soljacic M (2007) Wireless power transfer via strongly coupled magnetic resonances. Science 317(5834):83–86

    Article  MathSciNet  Google Scholar 

  8. Sudevalayam S, Kulkarni P (2010) Energy harvesting sensor nodes: survey and implications. IEEE Commun Surv Tutor 13(3):443–461

    Article  Google Scholar 

  9. Qureshi B, Aziz SA, Wang X, Hawbani A, Alsamhi SH, Qureshi T, Naji A (2022) A state-of-the-art survey on wireless rechargeable sensor networks: perspectives and challenges. Wirel Netw 28(7):3019–3043

    Article  Google Scholar 

  10. Liu F, Lu S (2019) An energy-aware anchor point selection strategy for wireless rechargeable sensor networks. In: 2019 IEEE/CIC International Conference on Communications in China (ICCC). IEEE, pp 422–426

  11. Huong TT, Le Nguyen P, Binh HTT, Nguyenz K, Hai NM et al (2020) Genetic algorithm-based periodic charging scheme for energy depletion avoidance in WRSNs. In: 2020 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, pp 1–6

  12. Wang M, Zeng Y, Li J, Wang Y (2023) Collaborative energy optimization of multiple chargers based on node collaborative scheduling. Int J Distrib Sens Netw 2023(1):5092972

    Google Scholar 

  13. Habibi P, Hassanifard G, Ghaderzadeh A, Nosratpour A (2023) Offering a demand-based charging method using the GBO algorithm and fuzzy logic in the WRSN for wireless power transfer by UAV. J Sens 2023(1):6326423

    Article  Google Scholar 

  14. Sha C, Song D, Malekian R (2020) A periodic and distributed energy supplement method based on maximum recharging benefit in sensor networks. IEEE Internet Things J 8(4):2649–2669

    Article  Google Scholar 

  15. Liu R, Xie M, Liu A, Song H (2024) Joint optimization risk factor and energy consumption in IoT networks with TinyML-enabled internet of UAVs. IEEE Internet Things J

  16. Ren Y, Liu A, Mao X, Li F (2021) An intelligent charging scheme maximizing the utility for rechargeable network in smart city. Pervasive Mob Comput 77:101457

    Article  Google Scholar 

  17. Li J, Sun G, Wang A, Lei M, Liang S, Kang H, Liu Y (2022) A many-objective optimization charging scheme for wireless rechargeable sensor networks via mobile charging vehicles. Comput Netw 215:109196

    Article  Google Scholar 

  18. Zhu J, Feng Y, Liu M, Chen G, Huang Y (2018) Adaptive online mobile charging for node failure avoidance in wireless rechargeable sensor networks. Comput Commun 126:28–37

    Article  Google Scholar 

  19. Kumar R, Mukherjee JC (2021) On-demand vehicle-assisted charging in wireless rechargeable sensor networks. Ad Hoc Netw 112:102389

    Article  Google Scholar 

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

    Article  Google Scholar 

  21. Tomar A, Muduli L, Jana PK (2020) A fuzzy logic-based on-demand charging algorithm for wireless rechargeable sensor networks with multiple chargers. IEEE Trans Mob Comput 20(9):2715–2727

    Article  Google Scholar 

  22. Kumar N, Dash D, Kumar M (2021) An efficient on-demand charging schedule method in rechargeable sensor networks. J Ambient Intell Humaniz Comput 12:8041–8058

    Article  Google Scholar 

  23. Dudyala AK, Dash D (2023) A novel efficient on demand charging schedule for rechargeable wireless sensor networks. Computing 1–19

  24. Shahzad MK, Cho TH (2015) Extending the network lifetime by pre-deterministic key distribution in CCEF in wireless sensor networks. Wirel Netw 21:2799–2809

    Article  Google Scholar 

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Authors and Affiliations

  1. University of Calcutta, Kolkata, India

    Saurav Ghosh & Kanyaka Chakraborty

  2. Netaji Subhash Engineering College, Kolkata, India

    Piyali Bagchi Khatua

  3. University of Kalyani, Kalyani, India

    Utpal Biswas

Authors
  1. Saurav Ghosh
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  2. Kanyaka Chakraborty
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  3. Piyali Bagchi Khatua
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  4. Utpal Biswas
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Correspondence to Saurav Ghosh.

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Ghosh, S., Chakraborty, K., Khatua, P.B. et al. Efficient charging schedules in a rechargeable wireless sensor network with multiple chargers. J Supercomput 81, 298 (2025). https://doi.org/10.1007/s11227-024-06804-4

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  • DOI: https://doi.org/10.1007/s11227-024-06804-4

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