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Metaheuristic Optimization Based Node Localization and Multihop Routing Scheme with Mobile Sink for Wireless Sensor Networks

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Abstract

Wireless Sensor Network (WSN) is composed of independent sensor nodes (SNs) that undergo random deployment in a particular region to sense the atmosphere effectively. The WSNs are applied in real-time applications like medical sector, home automation, traffic monitoring, and ecological observation. Meanwhile the SNs in WSN are energy constrained, routing process is considered as an effective way in achieving energy efficiency and maximize network lifetime. At the same time, node localization (NL) is also a critical challenge in WSN, which aims to analyze the geographical coordinate of unknown nodes through anchor nodes (ACN). Therefore, NL and routing processes are considered NP hard problems and resolved by the use of metaheuristic optimization algorithm. The study proposes a metaheuristic optimization based NL and multihop routing protocol with mobile sink (MONL-MRPMS) for WSN. The proposed MONL-MRPMS technique aims to achieve energy efficacy with accurate NL performance. The MONL-MRPMS technique involves an efficient Coyote Optimization Algorithm (COA) for NL, (COA-NL) in WSNs, assist in determining the location of the nodes iteratively by taking Euclidian distance as fitness into account. Besides, sea gull optimization based Multihop routing (SGO-MHR) protocol is designed for the optimum selection of routes for intercluster transmission. Eventually, a mobile sink (MS) with route adjustment technique is employed for improved energy efficiency of the WSN, which allows adjusting the routes depending upon the movement of MS. A wide-ranging experiments were performed and the obtained results emphasized the supremacy of MONL-MRPMS algorithm over the recent approaches.

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References

  1. Javed, I., Tang, X., Shaukat, K., Sarwar, M.U., Alam, T.M., Hameed, I.A. and Saleem, M.A., (2021). V2X-Based Mobile Localization in 3D Wireless Sensor Network. Security and Communication Networks, 2021.

  2. Uthayakumar, J., Elhoseny, M., & Shankar, K. (2020). Highly reliable and low-complexity image compression scheme using neighborhood correlation sequence algorithm in WSN. IEEE Transactions on Reliability, 69(4), 1398–1423.

    Article  Google Scholar 

  3. Arjunan, S., Pothula, S., & Ponnurangam, D. (2018). F5N-based unequal clustering protocol (F5NUCP) for wireless sensor networks. International Journal of Communication Systems, 31(17), e3811.

    Article  Google Scholar 

  4. Mohamed, R. E., Saleh, A. I., Abdelrazzak, M., & Samra, A. S. (2018). Survey on wireless sensor network applications and energy efficient routing protocols. Wireless Personal Communications, 101(2), 1019–1055.

    Article  Google Scholar 

  5. Uthayakumar, J., Vengattaraman, T., & Dhavachelvan, P. (2019). A new lossless neighborhood indexing sequence (NIS) algorithm for data compression in wireless sensor networks. Ad Hoc Networks, 83, 149–157.

    Article  Google Scholar 

  6. Ahmad, T., Li, X.J. and Seet, B.C., (2018) 3D localization using social network analysis for wireless sensor networks. In 2018 IEEE 3rd international conference on communication and information systems (ICCIS) (pp. 88–92). IEEE.

  7. Vinitha, A. and Rukmini, M.S.S., (2019). Secure and energy aware multi-hop routing protocol in WSN using Taylor-based hybrid optimization algorithm. Journal of King Saud University-Computer and Information Sciences.

  8. Mohan, R., Ananthula, V.R., 2019. Mohan, R., Ananthula, V.R., 2019 Reputation-based secure routing protocol in mobile ad-hoc network using Jaya Cuckoo optimization. International Journal of Modeling, Simulation, and Scientific Computing, 10: 195001

  9. Arjunan, S., & Sujatha, P. (2018). Lifetime maximization of wireless sensor network using fuzzy based unequal clustering and ACO based routing hybrid protocol. Applied Intelligence, 48(8), 2229–2246.

    Article  Google Scholar 

  10. Buvanesvari, M., Uthayakumar, J., & Amudhavel, J. (2017). Fuzzy based clustering to maximize network lifetime in wireless mobile sensor networks. JARDCS, 2017, 2156–2167.

    Google Scholar 

  11. Maheswari, U. (2018). A survey on recent techniques for energy efficient routing in WSN. Int. J. Sens. Sens. Networks, 6(1), 8.

    Article  Google Scholar 

  12. Kulkarni, V. R., Desai, V., & Kulkarni, R. V. (2019). A comparative investigation of deterministic and metaheuristic algorithms for node localization in wireless sensor networks. Wireless Networks, 25(5), 2789–2803.

    Article  Google Scholar 

  13. Strumberger, I., Minovic, M., Tuba, M., & Bacanin, N. (2019). Performance of elephant herding optimization and tree growth algorithm adapted for node localization in wireless sensor networks. Sensors, 19(11), 2515.

    Article  Google Scholar 

  14. Kanoosh, H.M., Houssein, E.H. and Selim, M.M., (2019). Salp swarm algorithm for node localization in wireless sensor networks. Journal of Computer Networks and Communications, 2019.

  15. Han, D., Yu, Y., Li, K. C., & de Mello, R. F. (2020). Enhancing the sensor node localization algorithm based on improved DV-hop and DE algorithms in wireless sensor Networks. Sensors, 20(2), 343.

    Article  Google Scholar 

  16. Mihoubi, M., Rahmoun, A., Lorenz, P., & Lasla, N. (2018). An effective Bat algorithm for node localization in distributed wireless sensor network. Security and Privacy, 1(1), e7.

    Article  Google Scholar 

  17. Mihoubi, M., Rahmoun, A., Zerkouk, M., Lorenz, P., & Baidar, L. (2020). Intelligent technique based on enhanced metaheuristic for optimization problem in internet of things and wireless sensor network. International Journal of Grid and High Performance Computing (IJGHPC), 12(3), 17–42.

    Article  Google Scholar 

  18. Yadav, R.K., Verma, S. and Venkatesan, S., (2021). iHRNL: Iterative Hessian-based manifold regularization mechanism for localization in WSN. The Journal of Supercomputing, pp.1–24.

  19. Wu, H., Liu, J., Dong, Z. and Liu, Y., (2020). A hybrid mobile node localization algorithm based on adaptive MCB-PSO approach in wireless sensor networks. Wireless communications and mobile computing, 2020.

  20. Sahoo, B. M., Pandey, H. M., & Amgoth, T. (2021). GAPSO-H: A hybrid approach towards optimizing the cluster based routing in wireless sensor network. Swarm and Evolutionary Computation, 60, 100772.

    Article  Google Scholar 

  21. Wang, H., Li, K., & Pedrycz, W. (2020). An elite hybrid metaheuristic optimization algorithm for maximizing wireless sensor networks lifetime with a sink node. IEEE Sensors Journal, 20(10), 5634–5649.

    Article  Google Scholar 

  22. Barzin, A., Sadegheih, A., Zare, H. K., & Honarvar, M. (2020). A hybrid swarm intelligence algorithm for clustering-based routing in wireless sensor networks. Journal of Circuits, Systems and Computers, 29(10), 2050163.

    Article  Google Scholar 

  23. Vinodhini, R., & Gomathy, C. (2020). MOMHR: A dynamic multi-hop routing protocol for WSN using heuristic based multi-objective function. Wireless Personal Communications, 111(2), 883–907.

    Article  Google Scholar 

  24. Singh, S., Nandan, A.S., Malik, A., Kumar, N. and Barnawi, A., (2021). An energy-efficient modified metaheuristic inspired algorithm for disaster management system using WSNs. IEEE Sensors Journal.

  25. BENMAHDI, M.B. and LEHSAINI, M., (2020). A GA-based multihop routing scheme using k-means clustering approach for wireless sensor networks. In 2020 Second International Conference on Embedded & Distributed Systems (EDiS) (pp. 155–160). IEEE.

  26. Vinitha, A., Rukmini, M. S. S., & Sunehra, D. (2020). Energy-efficient multihop routing in WSN using the hybrid optimization algorithm. International Journal of Communication Systems, 33(12), e4440.

    Article  Google Scholar 

  27. Rathore, R. S., Sangwan, S., Prakash, S., Adhikari, K., Kharel, R., & Cao, Y. (2020). Hybrid WGWO: Whale grey wolf optimization-based novel energy-efficient clustering for EH-WSNs. EURASIP Journal on Wireless Communications and Networking, 2020, 1–28.

    Article  Google Scholar 

  28. Nguyen, T. T., Nguyen, T. T., Nguyen, N. A., & Duong, T. L. (2021). A novel method based on coyote algorithm for simultaneous network reconfiguration and distribution generation placement. Ain Shams Engineering Journal, 12(1), 665–676.

    Article  MathSciNet  Google Scholar 

  29. Che, Y. and He, D., (2021). A Hybrid Whale Optimization with Seagull Algorithm for Global Optimization Problems. Mathematical Problems in Engineering, 2021.

  30. Sekhar, P., Lydia, E. L., Elhoseny, M., Al-Akaidi, M., Selim, M. M., & Shankar, K. (2021). An effective metaheuristic based node localization technique for wireless sensor networks enabled indoor communication. Physical Communication, 48, 101411.

    Article  Google Scholar 

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Acknowledgements

The authors gratefully acknowledge their respective organizations for their help and support. The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University (KKU), Kingdom of Saudi Arabia for funding this work through General Research Project under the grant number (RGP1/70/44).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Velammal Institute of Technology, Chennai, 601204, India

    S. Soundararajan

  2. Department of Computer Science and Engineering, QIS College of Engineering and Technology, Ongole, 523272, India

    Chinnarao Kurangi

  3. Department of Computer Science, Jeppiaar College of Arts and Science, Chennai, 603103, India

    Anwer Basha

  4. Genesys Academy of Computer Science, Puducherry, 605001, India

    J. Uthayakumar

  5. Department of EIE, Easwari Engineering College, Chennai, 600089, India

    K. Kalaivani

  6. ECE Department, M.Kumarasamy College of Engineering, Karur, Tamilnadu, 639113, India

    M. Dhamodaran

  7. Electrical Engineering Department, King Khalid University, Abha, 62529, Saudi Arabia

    Neeraj Kumar Shukla

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  1. S. Soundararajan
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  2. Chinnarao Kurangi
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  3. Anwer Basha
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  4. J. Uthayakumar
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  5. K. Kalaivani
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Correspondence to J. Uthayakumar.

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Soundararajan, S., Kurangi, C., Basha, A. et al. Metaheuristic Optimization Based Node Localization and Multihop Routing Scheme with Mobile Sink for Wireless Sensor Networks. Wireless Pers Commun 129, 2583–2605 (2023). https://doi.org/10.1007/s11277-023-10247-0

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  • DOI: https://doi.org/10.1007/s11277-023-10247-0

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