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Genetic Algorithm Based LEACH Protocol for Cluster Head Selection to Enhance The Network Lifetime of Wireless Sensor Network


Affiliations
1 Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, India
     

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Increased interest in the usage and deployment of Wireless Sensor Networks (WSN) has resulted in the development of a slew of novel routing protocols, all of which place a premium on energy efficiency. The most challenging aspect of wireless sensor network is surviving for an extended period using energy efficiently. To make the network last longer, the protocols must be energy efficient. In Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, Cluster Head (CH) selection is based on a random probability equation, and has limitations such as unequal distribution of clusters and energy, and random selection of CH. In order to solve these limitations, a method is proposed for improving CH selection and reducing CH energy degradation. The proposed algorithm, LEACH-CHGA protocol strengthens CH selection compared to the existing protocol while simultaneously lowering network energy usage. The optimal CH selection based on a genetic algorithm enhances network lifetime and energy consumption as compare to LEACH.

Keywords

LEACH, Genetic Algorithm, Cluster Head Selection, Network Lifetime, Blend-Crossover.
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  • A.A. Abbasi, “A Survey on Clustering Algorithms for Wireless Sensor Networks”, Computer Communications, Vol. 30, No. 14-15, pp. 2826-2841, 2007.

  • I.F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, “Wireless Sensor Networks: A Survey”, Computer Networks, Vol. 38, No. 4, pp. 393-422, 2002.

  • G. Anastasi, M. Conti, M. Di Francesco and A. Passarella, “Energy Conservation in Wireless Sensor Networks: A Survey”, Ad Hoc Networks, Vol. 7, No. 3, pp. 537-568, 2009.

  • T. Rault, A. Bouabdallah and Y. Challal, “Energy Efficiency in Wireless Sensor Networks: A Top-Down Survey”, Computer Networks, Vol. 67, pp. 104-122, 2014.

  • Neha Saini and Jasmeet Singh, “A Survey: Hierarchal Routing Protocol in Wireless Sensor Networks”, Global Journal of Computer Science and Technology: E Network, Web and Security, Vol. 14, No. 1, pp. 1-8, 2014.

  • J. Wan, D. Yuan and X. Xu, “A Review of Routing Protocols in Wireless Sensor Networks”, Proceedings of International Conference on Wireless Communications, Networking and Mobile Computing, pp. 1-4, 2008.

  • H.S. Bazzi, A.M. Haidar and A. Bilal, “Classification of Routing Protocols in Wireless Sensor Network”, Proceedings of International Conference on Computer Vision Image Analysis, pp. 1-8, 2015.

  • S. Anjali and M. Sharma, “Wireless Sensor Networks: Routing Protocols and Security Issues”, Proceedings of International Conference on Computer Communication Networking Technologies, pp. 3-7, 2014.

  • V. Kumar, S.B. Dhok, R. Tripathi and S. Tiwari, “A Review Study of Hierarchical Clustering Algorithms for Wireless Sensor Networks”, International Journal on Computer Science, Vol. 11, No. 3, pp. 92-101, 2014.

  • X. Liu, “A Typical Hierarchical Routing Protocols for Wireless Sensor Networks: A Review”, IEEE Sensors, Vol. 15, No. 10, pp. 5372-5383, 2015.

  • W.R. Heinzelman, A. Chandrakasan and H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks”, Proceedings of 33rd Annual Hawaii International Conference on System Sciences, pp. 1-10, 2000.

  • N. Sabor, S. Sasaki, M. Abo Zahhad and S.M. Ahmed, “A Comprehensive Survey on Hierarchical-Based Routing Protocols for Mobile Wireless Sensor Networks: Review, Taxonomy, and Future Directions”, Wireless Communications and Mobile Computing, Vol. 2017, pp. 1-19, 2017.

  • J. Hong, J. Kook, S. Lee, D. Kwon and S. Yi, “T-LEACH: The Method of Threshold-Based Cluster Head Replacement for Wireless Sensor Networks”, Information Systems Frontiers, Vol. 11, No. 5, pp. 513-521, 2009.

  • A. Salim, W. Osamy and A.M. Khedr, “IBLEACH: Intra-Balanced LEACH Protocol for Wireless Sensor Networks”, Wireless Networks, Vol. 20, No. 6, pp. 1515-1525, 2014.

  • W. Abushiba, P. Johnson, S. Alharthi and C. Wright, “An Energy Efficient and Adaptive Clustering for Wireless Sensor Network (CH-Leach) using Leach Protocol”, Proceedings of International Conference on Computer Engineering, pp. 50-54, 2017.

  • G.R. Annushakumar and V. Padmathilagam, “Analysis and Implementation of Q-Leach Protocol Based on Genetic Algorithm for WSN”, International Journal of Scientific Research in Science, Engineering and Technology, Vol. 5, No. 3, pp. 1-12, 2018.

  • Hongxia Miao, Xuanxuan Xiao, Bensheng Qi and Kang Wang, “Improvement and Application of LEACH Protocol based on Genetic Algorithm for WSN”, Proceedings of International Workshop on Computer Aided Modelling and Design of Communication Links and Networks, pp. 242-245, 2015.

  • A. Peiravi, H.R. Mashhadi and S. Hamed Javadi, “An Optimal Energy-Efficient Clustering Method in Wireless Sensor Networks using Multi-Objective Genetic Algorithm”, International Journal of Communication Systems, Vol. 26, No. 1, pp. 114-126, 2013.

  • R. Pachlor and D. Shrimankar, “VCH-ECCR: A Centralized Routing Protocol for Wireless Sensor Networks”, Sensors, Vol. 2017, No. 3, pp. 1-10, 2017.

  • J. Liu and C.V Ravishankar, “LEACH-GA: Genetic Algorithm-Based Energy-Efficient Adaptive Clustering Protocol for Wireless Sensor Networks”, International Journal of Machine Learning and Computing, Vol. 1, No. 12, pp. 79-85, 2011.

  • P. Sivakumar and M. Radhika, “Performance Analysis of LEACH-GA over LEACH and LEACH-C in WSN”, Procedia Computer Science, Vol. 125, pp. 248-256, 2018.

  • M. Abo-Zahhad, S.M. Ahmed, N. Sabor and S. Sasaki, “A New Energy-Efficient Adaptive Clustering Protocol Based on Genetic Algorithm for Improving the Lifetime and the Stable Period of Wireless Sensor Networks”, International Journal of Energy Information and Communications, Vol. 5, No. 3, pp. 47-72, 2014.

  • T. Bhatia, S. Kansal, S. Goel and A.K. Verma, “A Genetic Algorithm based Distance-Aware Routing Protocol for Wireless Sensor Networks”, Computer and Electrical Engineering, Vol. 56, pp. 441-455, 2016.

  • A. Khunteta and A. Bajpai, “Genetic Algorithm with Leach Protocol for Cluster Head Selection in Wireless Sensor Networks”, ICTACT Journal on Communication Technology, Vol. 11, No. 2, pp. 2182-2186, 2020.

  • A. Bari, S. Wazed, A. Jaekel and S. Bandyopadhyay, “A Genetic Algorithm based Approach for Energy Efficient Routing in Two-Tiered Sensor Networks”, Ad Hoc Networks, Vol. 7, No. 4, pp. 665-676, 2009.

  • T.V. Mathew, “Genetic Algorithm”, Available at: https://datajobs.com/data-science-repo/Genetic-Algorithm-Guide-Tom-Mathew.pdf, Accessed at 2021.

  • T.D. Gwiazda, “Blend (BLX) Crossover”, Available at: http://www.tomaszgwiazda.com/blendX.htm, Accessed at 2021.


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  • Genetic Algorithm Based LEACH Protocol for Cluster Head Selection to Enhance The Network Lifetime of Wireless Sensor Network

Abstract Views: 297  |  PDF Views: 1

Authors

Manisha Kumari
Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, India
Gurjinder Kaur
Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, India

Abstract


Increased interest in the usage and deployment of Wireless Sensor Networks (WSN) has resulted in the development of a slew of novel routing protocols, all of which place a premium on energy efficiency. The most challenging aspect of wireless sensor network is surviving for an extended period using energy efficiently. To make the network last longer, the protocols must be energy efficient. In Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, Cluster Head (CH) selection is based on a random probability equation, and has limitations such as unequal distribution of clusters and energy, and random selection of CH. In order to solve these limitations, a method is proposed for improving CH selection and reducing CH energy degradation. The proposed algorithm, LEACH-CHGA protocol strengthens CH selection compared to the existing protocol while simultaneously lowering network energy usage. The optimal CH selection based on a genetic algorithm enhances network lifetime and energy consumption as compare to LEACH.

Keywords


LEACH, Genetic Algorithm, Cluster Head Selection, Network Lifetime, Blend-Crossover.

References