ICTACT Journal on Communication Technology

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Reliable and Energy Efficient Cluster Head Selection Using Evolutionary Algorithm in Wireless Sensor Network


Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India., India
     

   Subscribe/Renew Journal


One of the most pressing problems in the industry at the moment is figuring out how to make wireless sensor networks (WSN) more reliable and extend their lifespan. The processes of selection and the development of clusters are incredibly significant; however, carrying them out is challenging and time-consuming despite the significance of the tasks. In the most recent study, researchers began their hunt by selecting a particular cluster head to use as a basis for their investigation. On the other hand, the model that was suggested utilizes evolutionary cluster head selection as one of its components. This contributes to the acceleration of computing, the improvement of selection precision, and the prevention of the selection of duplicate nodes. When the results of the simulation of the suggested model are compared to the results of simulations using other methods and techniques, we find that our method is both more accurate and more efficient. This was discovered when the results of the simulation of the proposed model were compared to the results of simulations using other approaches and techniques.

Keywords

Cluster, WSN, Nodes, Network Lifetime.
Subscription Login to verify subscription
User
Notifications
Font Size

  • R. Ramya and T. Brindha, “A Comprehensive Review on Optimal Cluster Head Selection in WSN-IoT”, Advances in Engineering Software, Vol. 171, pp. 103170-103187, 2022.

  • R.K. Yadav and R.P. Mahapatra, “Hybrid Metaheuristic Algorithm for Optimal Cluster Head Selection in Wireless Sensor Network”, Pervasive and Mobile Computing, Vol. 79, pp. 101504-101515, 2022.

  • V. Narayan, “FBCHS: Fuzzy Based Cluster Head Selection Protocol to Enhance Network Lifetime of WSN”, Advances in Distributed Computing and Artificial Intelligence Journal, Vol. 11, No. 3, pp. 285-307, 2022.

  • S. Karunakaran and P. Thangaraj, “A Cluster-Based Service Discovery Protocol for Mobile Ad-hoc Networks”, American Journal of Scientific Research, No. 11, pp. 179- 190, 2011.

  • Danish Shehzad, Waqar Ishaq, Zakir Khan and Junaid Iqbal, “An Enhanced Weight Based Clustering Algorithm for Mobile Adhoc Networks”, Proceedings of International conference on Computer Science and Information Systems, pp. 116-118, 2014.

  • Abbas Karimi, Abbas Afsharfarnia, Faraneh Zarafshan and S. A. R. Al-Haddad, “A Novel Clustering Algorithm for Mobile Ad Hoc Networks Based on Determination of Virtual Links Weight to Increase Network Stability”, The Scientific World Journal, Vol. 2014, pp. 1-11, 2014.

  • Asis Kumar Tripathy and Suchismita Chinara, “Comparison of Residual Energy-Based Clustering Algorithms for Wireless Sensor Network”, International Scholarly Research Network, ISRN Sensor Networks, Vol. 2012, pp. 1-10, 2012.

  • Mohamed Aissa and Abdelfettah Belghith, “A Node Quality based Clustering Algorithm in Wireless Mobile AdHoc Networks”, Proceedings of International Conference on Ambient Systems, Networks and Technologies, Vol. 32, pp. 174 – 181, 2014.

  • G. Ran, “Improving on LEACH Protocol of Wireless Sensor Networks using Fuzzy Logic”, Journal of Information and Computational Science, Vol. 7, No. 3, pp. 767-775, 2010.

  • B. Singh and D.K. Lobiyal, “A Novel Energy-Aware Cluster Head Selection based on Particle Swarm Optimization for Wireless Sensor Networks”, Human-Centric Computing and Information Sciences, Vol. 2, No. 1, pp. 1-18, 2012.

  • N.A. Latiff, “Energy-Aware Clustering for Wireless Sensor Networks using Particle Swarm Optimization”, Proceedings of IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1-5, 2007.

  • P.C. Srinivasa Rao and H. Banka, “Novel Chemical Reaction Optimization based Unequal Clustering and Routing Algorithms for Wireless Sensor Networks”, Wireless Networks, Vol. 23, pp. 759-778, 2017.

  • P.C. Srinivasa Rao and H. Banka, “Energy Efficient Clustering Algorithms for Wireless Sensor Networks: Novel Chemical Reaction Optimization Approach”, Wireless Networks, Vol. 23, pp. 433-452, 2017.

  • H. Banka and P.K. Jana, “PSO-Based Multiple-Sink Placement Algorithm for Protracting the Lifetime of Wireless Sensor Networks”, Proceedings of International Conference on Computer and Communication Technologies, pp. 605-616, 2016.


Abstract Views: 164

PDF Views: 0




  • Reliable and Energy Efficient Cluster Head Selection Using Evolutionary Algorithm in Wireless Sensor Network

Abstract Views: 164  |  PDF Views: 0

Authors

S. Mageshwaran
Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India., India
P. Sivananaintha Perumal
Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India., India
R.S. Rajesh
Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India., India
P. Sundareswaran
Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India., India

Abstract


One of the most pressing problems in the industry at the moment is figuring out how to make wireless sensor networks (WSN) more reliable and extend their lifespan. The processes of selection and the development of clusters are incredibly significant; however, carrying them out is challenging and time-consuming despite the significance of the tasks. In the most recent study, researchers began their hunt by selecting a particular cluster head to use as a basis for their investigation. On the other hand, the model that was suggested utilizes evolutionary cluster head selection as one of its components. This contributes to the acceleration of computing, the improvement of selection precision, and the prevention of the selection of duplicate nodes. When the results of the simulation of the suggested model are compared to the results of simulations using other methods and techniques, we find that our method is both more accurate and more efficient. This was discovered when the results of the simulation of the proposed model were compared to the results of simulations using other approaches and techniques.

Keywords


Cluster, WSN, Nodes, Network Lifetime.

References