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

Genetic Algorithm with Leach Protocol for Cluster Head Selection in Wireless Sensor Networks


Affiliations
1 Department of Electronics Engineering, Rajasthan Technical University, Kota, India
     

   Subscribe/Renew Journal


Wireless Sensor Network (WSN) is the deployed randomly and on the far places to sense information. The security, quality of service and energy consumption is the major issues of WSN. To minimize the consumption of higher amount of energy in these networks, clustering is applied. The Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is used for the cluster head selection in the network. The cluster head is selected based on the energy consumption and distance to base station. A node is selected as Cluster Head (CH) if it has the highest amount of energy and the least distance from base station. In this research work, genetic algorithm is applied with the LEACH protocol for the cluster head selection. The proposed work is implemented in Matlab. The results of existing LEACH protocol is compared with proposed LEACH protocol in terms of certain parameters. The comparative analysis and achieved outcomes show that the proposed approach performs well in terms of energy consumption as it consumes lesser amount of energy.

Keywords

LEACH, Clustering, Genetic Algorithm, Cluster Head.
Subscription Login to verify subscription
User
Notifications
Font Size

  • B.K. Panigrahi and V. Ravikumar Pandi, “Bacterial Foraging Optimisation: Nelder–Mead Hybrid Algorithm for Economic Load Dispatch”, IET Generation Transmission Distribution, Vol. 2, No. 4, pp. 556-565, 2008.
  • H. Shen, Y.L. Zhu, X.M. Zhou, H.F. Guo, C.G. Chang, “Bacterial Foraging Optimization Algorithm with Particle Swarm Optimization Strategy for Global Numerical Optimization”, Proceedings of World Summit on Genetic and Evolutionary Computation, pp. 497-504, 2009.
  • Ramin Yarinezhada and Amir Sarabi, “Reducing Delay and Energy Consumption in Wireless Sensor Networks by making Virtual Grid Infrastructure and using Mobile Sink”, International Journal of Electronics and Communications, Vol. 84, pp. 144-152, 2018.
  • Abhishek Chunawale and Sumedha Sirsikar, “Minimization of Average Energy Consumption to Prolong Lifetime of Wireless Sensor Network”, Proceedings of IEEE Global Conference on Wireless Computing and Networking, pp. 1-6, 2014.
  • Jiaying Song and Yen Kheng Tan, “Energy Consumption Analysis of ZigBee-Based Energy Harvesting Wireless Sensor Networks”, Proceedings of IEEE International Conference on Communication Systems, pp. 21-29, 2012.
  • Changjiang Jiang, Yun Ren, Yuwei Zhou and Hancheng Zhang, “Low-Energy Consumption Uneven Clustering Routing Protocol for Wireless Sensor Networks”, Proceedings of 8th International Conference on Intelligent Human-Machine Systems and Cybernetics, pp. 1-8, 2016.
  • P. Murali, A. Challa, M.R. Kasyap and Chittaranjan Hota, “A Generalized Energy Consumption Model for Wireless Sensor Networks”, Proceedings of International Conference on Computational Intelligence and Communication Networks, pp. 233-239, 2010.
  • Bin Li, Wenjie Wang, Qinye Yin, Rong Yang, Yubo Li and Chen Wang, “A New Cooperative Transmission Metric in Wireless Sensor Networks to Minimize Energy Consumption per Unit Transmit Distance”, IEEE Communications Letters, Vol. 16, No. 5, pp. 626-629, 2012.
  • Jie Huang, “Research on Balanced Energy Consumption of Wireless Sensor Network Nodes Based on Clustering Algorithm”, Proceedings of International Conference on Computer Network, Electronic and Automation, pp. 1-6, 2017.
  • Ashfaq Ahmad, Nadeem Javaid, Muhammad Imran, Mohsen Guizani and Ahmad A. Alhamed, “An Advanced Energy Consumption Model for Terrestrial Wireless Sensor Networks”, Proceedings of International Wireless Communications and Mobile Computing Conference, pp. 1-8, 2016.
  • K. Praghash and R. Ravi, “Energy Consumption Architecture for Wireless Sensor Networks with Different Clusters”, Proceedings of 3rd International Conference on Science Technology Engineering and Management, pp. 441-446, 2017.
  • Shuang Jia, Lin Ma and Danyang Qin, “Research on Low Energy Consumption Distributed Fault Detection Mechanism in Wireless Sensor Network”, China Communications, Vol. 16, No. 3, pp. 179-189, 2019.
  • Bingyue Liu, “An Energy Consumption Control Scheme based on Radial Basis Function in Wireless Sensor Networks”, Proceedings of International Conference on Intelligent Transportation, Big Data and Smart City, pp. 111-117, 2019.
  • Sabrine Khriji, Ahmed Yahia Kallel, Sandeep Reedy, Dhouha El Houssaini, Ines Kammoun and Olfa Kanoun, “Dynamic Autonomous Energy Consumption Measurement for a Wireless Sensor Node”, Proceedings of IEEE International Symposium on Measurements and Networking, pp. 1-6, 2019.
  • Marija Tutunovic and Pongpisit Wuttidittachotti, “Discovery of Suitable Node Number for Wireless Sensor Networks based on Energy Consumption using Cooja”, Proceedings of International Conference on Advanced Communication Technology, pp. 761-766, 2019.

Abstract Views: 248

PDF Views: 0




  • Genetic Algorithm with Leach Protocol for Cluster Head Selection in Wireless Sensor Networks

Abstract Views: 248  |  PDF Views: 0

Authors

Ajay Khunteta
Department of Electronics Engineering, Rajasthan Technical University, Kota, India
Anurag Bajpai
Department of Electronics Engineering, Rajasthan Technical University, Kota, India

Abstract


Wireless Sensor Network (WSN) is the deployed randomly and on the far places to sense information. The security, quality of service and energy consumption is the major issues of WSN. To minimize the consumption of higher amount of energy in these networks, clustering is applied. The Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is used for the cluster head selection in the network. The cluster head is selected based on the energy consumption and distance to base station. A node is selected as Cluster Head (CH) if it has the highest amount of energy and the least distance from base station. In this research work, genetic algorithm is applied with the LEACH protocol for the cluster head selection. The proposed work is implemented in Matlab. The results of existing LEACH protocol is compared with proposed LEACH protocol in terms of certain parameters. The comparative analysis and achieved outcomes show that the proposed approach performs well in terms of energy consumption as it consumes lesser amount of energy.

Keywords


LEACH, Clustering, Genetic Algorithm, Cluster Head.

References