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CSO Based Energy Efficient Cluster Protocol for Wireless Sensor Networks


Affiliations
1 School of Electrical Engineering, Vellore Institute of Technology, Vellore, India
     

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In wireless sensor networks (WSNs) energy saving has become one of the prime optimization problem and clustering technique has been considered as most efficient techniques to achieve the same. The selection of cluster heads (CHs) plays a vital role in hierarchical based WSNs as it consume more energy owing to its additional duty of receiving, aggregating the data from the cluster member nodes and transmitting the same to the base station (BS). Improper selection of CHs causes impact on network life time. In order to have an energy efficient network a suitable optimization algorithm is to be adopted to select the CHs. We propose a cluster protocol based on Cat Swarm Optimization (CSO) algorithm to reduce the energy consumption during cluster setup phase and transmission phase. The CSO cluster protocol is developed by considering intra-cluster distance of nodes to CH and residual energy of cluster member nodes. The algorithm is tested extensively on various scenarios of WSNs, varying number of sensor nodes and the CHs. The energy efficient scheme of proposed CSO performance is compared with other well-known protocols such as Low Energy Adaptive Clustering Hierarchy -Centralized (LEACH-C) and Particle Swarm Optimization (PSO) based protocol to prove the superiority of it.

Keywords

WSN, Cluster Head, Sensor Nodes, PSO, CSO.
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  • Ian F.Akyildiz, Weilian Su, Yogesh Sankarasubramaniam and Erdal Cayirci, “A Survey on Sensor Networks”, IEEE Communications Magazine, Vol. 40, No. 8, pp. 102-114, 2002.

  • Kemal Akkaya and Mohamed Younis, “A Survey on Routing Protocols for Wireless Sensor Networks”, Ad Hoc Networks, Vol. 3, No. 3, pp. 325-349, 2005.

  • W.B. Heinzelman et al., “Energy Efficient Communication Protocol for Wireless Micro Sensor Networks”, Proceedings of 33rd Hawaii International Conference on System Sciences, pp. 112-117, 2000.

  • X.Y. Liu et al., “CDC: Compressive Data Collection for Wireless Sensor Networks”, IEEE Transactions on Parallel and Distributed Systems, Vol. 26, No. 8, pp. 2188-2197, 2015.

  • L. Xiang et al., “Compressed Data Aggregation for Energy Efficient Wireless Sensor Networks”, Proceedings of 8th IEEE Communications Society Conference on Sensor, Mesh and Adhoc Communications and Networks, pp. 46-54, 2011.

  • X. Xu et al., “Hierarchical Data Aggregation using Compressive Sensing (HDACS) in WSNs”, ACM Transactions on Sensor Networks, Vol. 11, No. 3, pp. 45-59, 2015.

  • O. Younis and S. Fahmy, “HEED: Hybrid Energy Efficient Distributed Clustering Approach for Ad Hoc Sensor Networks”, IEEE Transactions on Mobile Computing, Vol. 3, No. 4, pp. 366-379, 2004.

  • S. Lindsey and C.S. Raghavendra, “PEGASIS: Power Efficient Gathering in Sensor Information Systems”, Proceedings of IEEE International Aerospace Conference, Vol. 3, pp. 1125-1130, 2002.

  • Y. Yanjun. Qing Cao and Athanasios V. Vasilakos, “EDAL: An Energy-Efficient, Delay Aware, and Lifetime-Balancing Data Collection Protocol for Heterogeneous Wireless Sensor Networks”, IEEE ACM Transactions on Networking, Vol. 23, No. 3, pp. 810-823, 2015.

  • Y. Yanjun. Qing Cao and Athanasios V. Vasilakos, “EDAL: An Energy Efficient, Delay-Aware and Lifetime-Balancing Data Collection Protocol for Wireless Sensor Networks”, Proceedings of 10th International Conference on Mobile Ad hoc and Sensor Systems, pp. 182-190, 2013.

  • G. Wei et al., “Prediction-based Data Aggregation in Wireless Sensor Networks: Combining Grey Model and Kalman Filter”, Computer Communications, Vol. 34, No. 6, pp. 793-802, 2011.

  • K. Han, “Algorithm Design for Data Communications in Duty Cycled Wireless Sensor Networks: A Survey”, IEEE Communications Magazine, Vol. 51, No. 7, pp. 107-113, 2013.

  • V. Loscri, “A Two-Level Hierarchy for Low-Energy Adaptive Clustering Hierarchy (TL-LEACH)”, Proceedings of IEEE International Conference on Vehicular Technology, Vol. 62, No. 3, pp. 1809-1815, 2005.

  • M. Xiaoyan, “Study and Design on Clustering Routing Protocols of Wireless Sensor Networks”, Ph.D Dissertation, Department of Control Science and Engineering, Zhejiang University, 2006.

  • M.B. Yassein, “Improvement of LEACH Protocol of Wireless Sensor Networks (VLEACH)”, International Journal of Digital Content Technologies and Applications, Vol. 3, No. 2, pp. 132-136, 2009.

  • X. Fan and S. Yulin, “Improvement on LEACH Protocol of Wireless Sensor Network”, Proceedings of International Conference on Sensor Technologies and Applications, pp. 260-264, 2007.

  • N. Zhu and A.V. Vasilakos, “A Generic Framework for Energy Evaluation on Wireless Sensor Networks”, Wireless Networks, Vol. 22, No. 4, pp. 1199-1220, 2015.

  • W.B. Heinzelman, A.P. Chandrakasan and H. Balakrishnan, “An Application Specific Protocol Architecture for Wireless Microsensor Networks”, IEEE Transactions on Wireless Communications, Vol. 1, No. 4, pp. 660-670, 2002.

  • J. Tillet, “Cluster Head Identification in Adhoc Sensor Networks using Particle Swarm Optimization”, Proceedings

  • of IEEE International Conference on Personal Wireless Communications, pp. 201-205, 2002.

  • S.M. Guru, S.K. Halgamuge and S. Fernando, “Particle Swarm Optimisers for Cluster Formation in Wireless Sensor Networks”, Proceedings of International Conference on Intelligent Sensors Sensor Networks and Information Processing, pp. 319-324, 2005.

  • N.M.A. Latiff, C.C. Tsimenidis and B.S. Sharif, “Energy-Aware Clustering for Wireless Sensor Networks using Particle Swarm Optimization”, Proceedings of 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1-5, 2007.

  • Buddha Singh and Daya Krishan 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. 2-13, 2012.

  • Duc Chinh Hoang, Parikshit Yadav, Rajesh Kumar and Sanjib Kumar Panda, “Real-Time Implementation of a Harmony Search Algorithm-based Clustering Protocol for Energy Efficient Wireless Sensor Networks”, IEEE Transactions on Industrial Informatics, Vol. 10, No. 1, pp. 774-783, 2014.

  • Shu-Chuan, Pei-Wei Tsai and Jeng-Shyang Pan, “Cat Swarm Optimization”, Proceedings of Pacific Rim International Conference on Artificial Intelligence, pp. 854-858, 2006.

  • Shu-Chuan and Pei-Wei Tsai, “Computational Intelligence based on the Behaviour of Cats”, International Journal of Innovative Computing, Information and Control, Vol. 3, No. 1, pp. 163-173, 2007.

  • Mahdi Bahrami, Omid Bozorg-Haddad and Xuefeng Chu, “Cat Swarm Optimization (CSO) Algorithm”, Proceedings of International Conference on Advanced Optimization by Nature-Inspired Algorithms, pp. 9-17, 2016.

  • Suman Kumar Saha, “Cat Swarm Optimization Algorithm for Optimal Linear Phase FIR Filter Design”, ISA Transactions, Vol. 52, No. 6, pp. 781-794, 2013.

  • D. Chandirasekaran and T. Jayabarathi, “Cat Swarm Algorithm in Wireless Sensor Networks for Optimized Cluster Head Selection: A Real Time Approach”, Cluster Computing, pp. 1-11, 2017.

  • D.C. Hoang, R. Kumar and S.K. Panda, “Fuzzy C-means Clustering Protocol for Wireless Sensor Networks”, Proceedings of IEEE International Symposium on Industrial Electronics, pp. 3477-3482, 2010.

  • J. So and W.K. Jenkins, “Comparison of Cat Swarm Optimization with Particle Swarm Optimization for IIR System Identification”, Proceedings of IEEE International Conference on Signals, Systems and Computers, pp. 903-910, 2013.


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  • CSO Based Energy Efficient Cluster Protocol for Wireless Sensor Networks

Abstract Views: 217  |  PDF Views: 3

Authors

D. Chandirasekaran
School of Electrical Engineering, Vellore Institute of Technology, Vellore, India
T. Jayabarathi
School of Electrical Engineering, Vellore Institute of Technology, Vellore, India

Abstract


In wireless sensor networks (WSNs) energy saving has become one of the prime optimization problem and clustering technique has been considered as most efficient techniques to achieve the same. The selection of cluster heads (CHs) plays a vital role in hierarchical based WSNs as it consume more energy owing to its additional duty of receiving, aggregating the data from the cluster member nodes and transmitting the same to the base station (BS). Improper selection of CHs causes impact on network life time. In order to have an energy efficient network a suitable optimization algorithm is to be adopted to select the CHs. We propose a cluster protocol based on Cat Swarm Optimization (CSO) algorithm to reduce the energy consumption during cluster setup phase and transmission phase. The CSO cluster protocol is developed by considering intra-cluster distance of nodes to CH and residual energy of cluster member nodes. The algorithm is tested extensively on various scenarios of WSNs, varying number of sensor nodes and the CHs. The energy efficient scheme of proposed CSO performance is compared with other well-known protocols such as Low Energy Adaptive Clustering Hierarchy -Centralized (LEACH-C) and Particle Swarm Optimization (PSO) based protocol to prove the superiority of it.

Keywords


WSN, Cluster Head, Sensor Nodes, PSO, CSO.

References