Skip to main content

Advertisement

SpringerLink
Log in

Hybridized Dragonfly and Jaya algorithm for optimal sensor node location identification in mobile wireless sensor networks

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

A wireless sensor network (WSN) consists of an extensive number of low-power sensor nodes to gather information from their environment and monitor physical activities. This makes node localization a crucial aspect in most WSN applications since measurement data is worthless unless the location from where the data is acquired is known precisely. The majority of localization solutions rely on anchor nodes for estimating the node locations with different localization accuracy, complexity, and hence different applicability. But, the cost and complexity in the localization of large-scale WSNs are not significantly reduced. In this paper, a novel Hybridized Dragonfly and Jaya Optimization technique (HyDAJ) is introduced for improving localization accuracy and performance of mobile WSNs. The proposed hybrid technique combines the advantages of Dragonfly algorithm and Jaya algorithm to localize the sensor nodes in a more efficient way and overcomes the limitations of the original algorithm. The hybrid algorithm verifies that all target nodes are precisely localized with higher accuracy. Simulation results reveal that HyDAJ outperforms existing methods under multiple metrics including localization efficiency, mean localization error, computation time, and energy consumption.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability statement

Data are available upon request.

References

  1. Walid O, El-Sawy Ahmed A, Khedr AM (2020) Effective TDMA scheduling for tree-based data collection using genetic algorithm in wireless sensor network. Peer-to-Peer Netw Appl 13:796–815

    Article  Google Scholar 

  2. Ahmed A, Walid O, Khedr AM, El-Sawy Ahmed A, Karan S (2020) Grey Wolf based compressive sensing scheme for data gathering in IoT based heterogeneous WSNs. Wirel Netw 26:3395–3418

    Article  Google Scholar 

  3. Khedr AM, PRPV (2020) An energy efficient data gathering protocol for heterogeneous mobile wireless sensor networks. In: 2020 17th International Multi-Conference on Systems, Signals & Devices (SSD), pp 366–371

  4. Pravija Raj PV, Khedr AM, Al Aghbari Z (2022) EDGO: UAV-based effective data gathering scheme for wireless sensor networks with obstacles. Wirel Netw 28:2499–2518

    Article  Google Scholar 

  5. Saad M, Abdallah S (2021) On spectrum-efficient routing in interference-limited full-duplex multihop wireless networks. IEEE Access 9:11134–11143

    Article  Google Scholar 

  6. Khedr AM, Pravija Raj PV (2020) An energy efficient data gathering protocol for heterogeneous mobile wireless sensor networks. In: 2020 17th International Multi-Conference on Systems, Signals & Devices (SSD), pp 366–371

  7. Pravija Raj PV, Khedr AM, Al Aghbari Z (2022) EDGO: UAV-based effective data gathering scheme for wireless sensor networks with obstacles. Wirel Netw 28:2499–2518

    Article  Google Scholar 

  8. Khedr AM, Walid O (2013) Minimum connected cover of a query region in heterogeneous wireless sensor networks. Inf Sci 223:153–163

    Article  MathSciNet  Google Scholar 

  9. Khedr AM, Omar Dina M (2015) SEP-CS: effective routing protocol for heterogeneous wireless sensor networks. Ad Hoc Sens Wirel Netw 26(1–4):211–234

    Google Scholar 

  10. Bhat Soumya J, Santhosh KV (2022) A localization and deployment model for wireless sensor networks using arithmetic optimization algorithm. Peer-to-Peer Netw Appl 15:1473–1485

    Article  Google Scholar 

  11. Wenxian J, Guohong Q, Menghan L, Jie Z (2022) A high accuracy localization algorithm with DV-Hop and fruit fly optimization in anisotropic wireless networks. J King Saud Univ Comput Inf Sci 34:1–10

    Google Scholar 

  12. Singh MS, Sonia G, Ranjit K (2022) Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration and exploitation characteristics. J Supercomput 78:11975–12023

    Article  Google Scholar 

  13. Mohar SS, Goyal S, Kaur R (2022) Optimum deployment of sensor nodes in wireless sensor network using hybrid fruit fly optimization algorithm and bat optimization algorithm for 3D environment. Peer-to-Peer Netw Appl 15:2694–2718

    Article  Google Scholar 

  14. Oruba A, Walid O, Mohamed S, Khedr Ahmed M (2023) Modified rat swarm optimization based localization algorithm for wireless sensor networks. Wirel Pers Commun Pers. https://doi.org/10.1007/s11277-023-10347-x

    Article  Google Scholar 

  15. Shivakumar K, Mathapati Basavaraj S (2022) Localization in wireless sensor network using machine learning optimal trained deep neural network by parametric analysis. Meas Sensors 24:1–5

    MATH  Google Scholar 

  16. Musikawana P, Kongsorota Y, Muneesawangb P, So-Ina C (2022) An enhanced obstacle-aware deployment scheme with an opposition-based competitive swarm optimizer for mobile WSNs. Expert Syst Appl 189:1–21

    Google Scholar 

  17. Najarro LA, Song I, Kim K (2022) Fundamental limitations and state-of-the-art solutions for target node localization in WSNs: a review. IEEE Sens J 22(24):23661–23682

    Article  Google Scholar 

  18. Farooq-I-Azam M, Ni Q, Ansari EA (2016) Intelligent energy-efficient localization using variable range beacons in industrial wireless sensor networks. IEEE Trans Industr Inf 12(6):2206–2216

    Article  Google Scholar 

  19. Yin F, Fritsche C, Jin D, Gustafsson F, Zoubir AM (2015) Cooperative localization in WSNs using Gaussian mixture modeling: distributed ECM algorithms. IEEE Trans Signal Process 63(6):1448–1463

    Article  Google Scholar 

  20. Nithya B, Jeyachidra J (2021) Hybrid ABC-BAT optimization algorithm for localization in HWSN. Microprocess Microsyst 1–18

  21. Qiaoh Y (2022) A new localization method based on improved particle swarm optimization for wireless sensor networks. IET Softw 16(3):251–258

    Article  Google Scholar 

  22. Qianqian R, Yang Z, Ioanis N, Jinbao L, Pana Yu (2020) RSSI quantization and genetic algorithm based localization in wireless sensor networks. Ad Hoc Netw 107:102255

    Article  Google Scholar 

  23. Al Maqbali B (2020) Sensor activation in WSN using improved cuckoo search and squirrel search algorithm. J Netw Commun Syst (JNACS) 3(2):27–35

    Article  Google Scholar 

  24. Kailu M, Keqiang Y, Junna S (2017) Wireless sensor network nodes localization method based on cellular automata bat algorithm. Telecommun 33(11):56–65

    Google Scholar 

  25. Sabale K, Saunhita S, Mini S (2021) Obstacle handling mechanism for mobile anchor assisted localization in wireless sensor networks. IEEE Sens J 21(19):21999–22010

    Article  Google Scholar 

  26. Zheng K, Huijian W, Hang L, Wei X, Lei L, Jian Q, Shen XS (2017) Energy-efficient localization and tracking of mobile devices in wireless sensor networks. IEEE Trans Veh Technol 66(3):2714–2726

    Article  Google Scholar 

  27. Kirtil HS, Seyyedabbasi A (2022) A Hybrid Metaheuristic Algorithm for the Localization Mobile Sensor Nodes. In: International Conference on Forthcoming Networks and Sustainability in the IoT Era, pp 40–52. Springer, Cham

  28. de Oliveira LL, Eisenkraemer Gabriel H, Carara Everton A, Martins João B, Josè M (2022) Mobile localization techniques for wireless sensor networks: survey and recommendations. ACM Trans Sens Netw (TOSN) 19(2):1–39

    Google Scholar 

  29. Reddy SV, Reddy ED, Amruta L, Reddy PS (2021) An efficient localization approach in wireless sensor networks using krill herd optimization algorithm. IEEE Syst J 15(2):2432–2442

    Article  Google Scholar 

  30. Lakshmi YV, Singh P, Abouhawwash M, Mahajan S, Pandit AK, Ahmed AB (2022) Improved chan algorithm based optimal UWB sensor node localization using hybrid particle swarm optimization. IEEE Access 10:32546–32565

    Article  Google Scholar 

  31. Mirjalili S (2016) Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Comput Appli 27:1053–1073

    Article  Google Scholar 

  32. Rao R (2016) Jaya: a simple and new optimization algorithm for solving constrained and unconstrained optimization problems. Int J Ind Eng Comput 7(1):19–34

    Google Scholar 

  33. Liang J, Wang L, Ji Q (2022) A particle swarm optimization algorithm for deployment of sensor nodes in WSN network. J Electr Comput Eng Hindawi 2022:1–12

    Google Scholar 

  34. Kumar MT, Kumar DD (2022) Improved wireless sensor network localization algorithm based on selective opposition class topper optimization (SOCTO). Wirel Pers Commun 128:1–25

    Google Scholar 

  35. Ouyang A, Yinsheng L, Liu Y, Wua M, Peng X (2021) An improved adaptive genetic algorithm based on DV-Hop for locating nodes in wireless sensor networks. Neurocomputing 458:500–510

    Article  Google Scholar 

  36. Karunanithy K, Velusamy B (2021) Directional antenna based node localization and reliable data collection mechanism using the local sink for wireless sensor networks. J Ind Inf Integr 24:1–14

    Google Scholar 

  37. Walid Osamy AM, Khedr AS, Ali AIA, El-Sawy AA (2022) Coverage, deployment and localization challenges in wireless sensor networks based on artificial intelligence techniques: a review. IEEE Access 10:30232–30257

    Article  Google Scholar 

  38. Walid O, Khedr AM, El-Sawy Ahmed A, Ahmed S, Dilna V (2021) IPDCA: intelligent proficient data collection approach for IoT-enabled wireless sensor networks in smart environments. Electronics 10:1–28

    Google Scholar 

  39. Ahmed A, Walid O, Khedr AM, Ahmed S (2021) Chain-routing scheme with compressive sensing-based data acquisition for Internet of Things-based wireless sensor networks. IET Netw 10:43–58

    Article  Google Scholar 

  40. Linqing G, Xiao F, Yang Z, Feng S, Thierry V (2020) Connectivity based DV-Hop localization for internet of things. IEEE 69(8):8949–8958

    Google Scholar 

  41. Ouyang Aijia L, Yinsheng LY, Meng W, Xuyu P (2021) An improved adaptive genetic algorithm based on DV-Hop for locating nodes in wireless sensor networks. Neurocomput 458:500–510

    Article  Google Scholar 

  42. Penghong W, Rui Z, Xiaopeng FS, Debin Z (2022) A distance estimation model for DV-hop localization in WSNs. IEEE 72:1–10

    Google Scholar 

  43. Mohar SS, Goyal S, Ranjit R (2021) Optimized sensor nodes deployment in wireless sensor network using bat algorithm. Wirel Pers Commun 116:2835–2853

    Article  Google Scholar 

Download references

Funding

None.

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Sharjah, Sharjah, 27272, UAE

    Ahmed M. Khedr, S. Sheeja Rani & Mohamed Saad

  2. Department of Computer Engineering, University of Sharjah, Sharjah, 27272, UAE

    Ahmed M. Khedr, S. Sheeja Rani & Mohamed Saad

  3. Mathematics Department, Zagazig University, Zagazig, Egypt

    Ahmed M. Khedr

Authors
  1. Ahmed M. Khedr
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Sheeja Rani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohamed Saad
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed equally to this work. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Ahmed M. Khedr.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Ethical approval

None.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khedr, A.M., Rani, S.S. & Saad, M. Hybridized Dragonfly and Jaya algorithm for optimal sensor node location identification in mobile wireless sensor networks. J Supercomput 79, 16940–16962 (2023). https://doi.org/10.1007/s11227-023-05326-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-023-05326-9

Keywords

Search

Navigation