Gray Wolf Optimization Based Clustering Using Network Parameters for WSN Applications

Year : 2026 | Volume : 16 | Issue : 02 | Page : 33 42
By

Simran Patkar,

Alok Mishra,

Aashu Kori,

  1. Student, Department of Electronics and Communication, Rameshwaram Institute of Technology & Management, Uttar Pradesh, India
  2. Assistant Professor, Department of Electronics and Communication, Rameshwaram Institute of Technology & Management, Uttar Pradesh, India
  3. Assistant Professor, Department of Electronics and Communication, Rameshwaram Institute of Technology & Management, Uttar Pradesh, India

Abstract

Modern communication systems need to use energy. This is very important for the Internet of things which’s a big network of smart devices that talk to each other. The Internet of Things is becoming very popular because it is useful. This paper is about a way to send data in a Wireless Sensor Network. We made a routing protocol that works well in a simulated environment. Our approach is to make the cluster head selection process better. We do this by using a technique that optimizes the process and compresses data at the cluster heads. We also made a system that chooses cluster heads in a specific way. This system uses an optimization strategy to make sure that sensor data is sent efficiently. We have developed an energy-efficient routing strategy to make the sensor networks last longer. Our new protocol uses less energy than traditional methods. This means that the sensor nodes last longer and the network lifetime is extended. The new protocol is better than protocols like LEACH and PEGASIS. It is 60% better when we measure the first node death round. It is also 20% better than the optimized DEEC routing protocol when it comes to energy efficiency. The Internet of Things and Wireless Sensor Networks will work better with our protocol.

Keywords: IoT, WSN, clustering, GWO, data compression, wavelet transform

[This article belongs to Journal of Communication Engineering & Systems ]

How to cite this article: Simran Patkar, Alok Mishra, Aashu Kori. Gray Wolf Optimization Based Clustering Using Network Parameters for WSN Applications. Journal of Communication Engineering & Systems. 2026; 16(02):33-42.
How to cite this URL: Simran Patkar, Alok Mishra, Aashu Kori. Gray Wolf Optimization Based Clustering Using Network Parameters for WSN Applications. Journal of Communication Engineering & Systems. 2026; 16(02):33-42. Available from: https://journals.stmjournals.com/joces/article=2026/view=259091

References

  1. Chaurasiya SK, Biswas A, Banerjee R. An energy-efficient clustering with mobile sink and rendezvous nodes for data collection in IoT-based wireless sensor networks. In: 2022 International Interdisciplinary Conference on Mathematics, Engineering and Science (MESIICON); 2022 Nov 11. 2022. p. 1-5.
  2. Abbad L, Nacer A, Abbad H, Brahim MT. Location-based Markov clustering routing protocol versus density-based clustering routing protocol for wireless sensor networks. In: 2022 International Symposium on iNnovative Informatics of Biskra (ISNIB); 2022 Dec 7. 2022. p. 1-6.
  3. Chaurasiya SK, Mondal S, Biswas A, Nayyar A, Shah MA, Banerjee R. An energy-efficient hybrid clustering technique (EEHCT) for IoT-based multilevel heterogeneous wireless sensor networks. IEEE Access. 2023;11:25941-58.
  4. Manchanda R, Bansal S. A review on WSN clustering algorithms in IoT-based applications. In: 2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES); 2023 Apr 28. 2023. p. 757-62.
  5. Sravanthi J, Subbayamma BV, Sultana W, Parabrahmachari S, Krishnan VG, Sriramam YS. Enhancement of energy efficiency using improved energy efficient routing protocol in wireless sensor networks for IoT applications. In: 2023 3rd International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS); 2023 May 18. 2023. p. 37-40.
  6. Vimal V, Singh KU, Kumar A, Gupta SK, Rashid M, Saket RK, et al. Clustering isolated nodes to enhance network’s lifetime of WSNs for IoT applications. IEEE Syst J. 2021;15(4):5654-63.
  7. Wason V, Kumar R, Johri P. Smart sensors network using IoT technologies. In: 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE); 2021 Mar 4. 2021. p. 65-8.
  8. Yin X, Guan L, Jiang D. A survey on LEACH-based clustering routing protocols in wireless sensor networks. In: 2022 International Conference on Education, Network and Information Technology (ICENIT); 2022 Sep 2. 2022. p. 323-5.
  9. Mishra J, Bagga J, Choubey S, Choubey A, Gupta K. Performance evaluation of cluster-based routing protocol used in wireless internet-of-things sensor networks. In: 2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT); 2021 Feb 19. 2021. p. 1-10.
  10. Mugerwa D, Nam Y, Choi H, Kwon Y, Lee E. Enhanced hybrid energy-efficient distributed clustering protocol for IoT-based WSNs with multiple sinks. In: 2023 IEEE Sensors Applications Symposium (SAS); 2023 Jul 18. 2023. p. 1-6.
  11. Shahraki A, Taherkordi A, Haugen Ø, Eliassen F. A survey and future directions on clustering: from WSNs to IoT and modern networking paradigms. IEEE Trans Netw Serv Manag. 2021;18(2):2242-74.
  12. Darabkh KA, Zomot JN, Al-Qudah Z, Khalifeh AF. Impairments-aware time slot allocation model for energy-constrained multi-hop clustered IoT nodes considering TDMA and DSSS MAC protocols. J Ind Inf Integr. 2022;25:100243.
  13. Thomson C, Wadhaj I, Tan Z, Al-Dubai A. Towards an energy balancing solution for wireless sensor network with mobile sink node. Comput Commun. 2021;170:50-64.
  14. Amutha J, Sharma S, Sharma SK. An energy efficient cluster based hybrid optimization algorithm with static sink and mobile sink node for wireless sensor networks. Expert Syst Appl. 2022;203:117334.
  15. Roy S, Mazumdar N, Pamula R. An energy and coverage sensitive approach to hierarchical data collection for mobile sink based wireless sensor networks. J Ambient Intell Humaniz Comput. 2021;12(1):1267-91.
  16. Verma RK, Jain S. Energy and delay efficient data acquisition in wireless sensor networks by selecting optimal visiting points for mobile sink. J Ambient Intell Humaniz Comput. 2023;14(9):11671-84.
  17. Gowda CS, Jayasree PV. Rendezvous points based energy-aware routing using hybrid neural network for mobile sink in wireless sensor networks. Wirel Netw. 2021;27(4):2961-76.
  18. Khafaga DS, Aldakheel EA, Khalid AM, Hamza HM, Hosny KM. Compression of bio-signals using block-based Haar wavelet transform and COVIDOA for IoMT systems. Bioengineering (Basel). 2023;10(4):406.
  19. Elyyan RR, Darabkh KA. A new IoT power-limited wireless sensor networks routing protocol utilizing computational intelligence. In: 2023 6th International Conference on Advanced Communication Technologies and Networking (CommNet); 2023 Dec 11. 2023. p. 1-7.

 

Regular Issue Subscription Original Research
Volume 16
Issue 02
Received 03/04/2026
Accepted 06/07/2026
Published 10/07/2026
Publication Time 98 Days

Login

My IP

PlumX Metrics

Support