Genetic Algorithm based Cluster Head Selection for Optimimized Communication in Wireless Sensor Network

Saravanan, Palani and Yarlagadda Venkata Subba, Rao and Kanampalli Sai Kiran, Reddy Genetic Algorithm based Cluster Head Selection for Optimimized Communication in Wireless Sensor Network. International Journal of Pure and Applied Mathematics, 2018, vol. 119, n. 12, pp. 13423-13435. [Journal article (Paginated)]

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English abstract

Wireless Sensor Network (WSNs) utilizes conveyed gadgets sensors for observing physical or natural conditions. It has been given to the steering conventions which may contrast contingent upon the application and system design. Vitality administration in WSN is of incomparable significance for the remotely sent vitality sensor hubs. The hubs can be obliged in the little gatherings called the Clusters. Clustering is done to accomplish the vitality effectiveness and the versatility of the system. Development of the group likewise includes the doling out the part to the hub based on their borders. In this paper, a novel strategy for cluster head selection based on Genetic Algorithm (GA) has been proposed. Every person in the GA populace speaks to a conceivable answer for the issue. Discovering people who are the best proposals to the enhancement issue and join these people into new people is a critical phase of the transformative procedure. The Cluster Head (CH) is picked using the proposed technique Genetic Algorithm based Cluster Head (GACH). The performance of the proposed system GACH has been compared with Particle Swarm Optimization Cluster Head (PSOCH). Simulations have been conducted with 14 wireless sensor nodes scattered around 8 kilometers. Results proves that GACH outperforms than PSOCH in terms of throughput, packet delivery ratio and energy efficiency.

Item type: Journal article (Paginated)
Keywords: Wireless Sensor Network, Clustering, Cluster Head selection, Particle Swarm Optimization, Genetic Algorithm
Subjects: B. Information use and sociology of information
B. Information use and sociology of information > BC. Information in society.
Depositing user: Raster Daster
Date deposited: 02 Aug 2018 07:31
Last modified: 02 Aug 2018 07:31
URI: http://hdl.handle.net/10760/33263

References

[1] Maraiya K, Kant K, Gupta N. Efficient Cluster Head Selection Scheme for Data Aggregation in Wireless Sensor Network. International Journal of Computer Applications, vol. 23, no. 9, June 2011.

[2] Hussain S, Matin AW, Islam O. Genetic algorithm for energy efficient clusters in wireless sensor networks. in Fourth International Conference on Information Technology: New Generations (ITNG 2007), April 2007.

[3] W. Liang, J. Luo, X. Xu, Prolonging network lifetime via a controlled mobile sink in wireless sensor networks, in: Proc. of IEEE Global Telecommunications Conference, 2010, pp. 1–6.

[4] K. Tian, B. Zhang, K. Huang, J. Ma, Data gathering protocols for wireless sensor networks with mobile sinks, in: Proc. of IEEE Global Telecommunications Conference, 2010, pp. 7–12.

[5] H. Salarian, K.W. Chin, F. Naghdy, An energy-efficient mobile-sink path selection strategy for wireless sensor networks, IEEE Trans. Veh. Technol. 63 (5) (2014) 2407–2419.

[6] Z. Lin, H. Zhang, Y. Wang, F. Yao, Energy-efficient routing protocol on mobile sink in wireless sensor network, Adv. Mater. Res. 787 (2013) 1050–1055.

[7] Y. Gu, Y. Ji, J. Li, B. Zhao, ESWC: Efficient scheduling for the mobile sink in wireless sensor networks with delay constraint, IEEE Trans. Parallel Distrib. Syst. 24 (7) (2013) 1310–1320.

[8] C. Tunca, S. Isik, M.Y. Donmez, C. Ersoy, Ring routing: An energy-efficient routing protocol for wireless sensor networks with a mobile sink, IEEE Trans. Mob. Comput. (2014) 1–14.

[9] S. M. Hosseinirad, S. K. Basu, (2012). Imperialist Approach to Cluster Head Selection in WSN, International Journal of Computer Applications, 1-5.

[10] Moslem AfrashtehMehr. (2011). Design and Implementation a New Energy Efficient Clustering Algorithm using Genetic Algorithm for Wireless Sensor Networks, World Academy of Science, Engineering and Technology, 430-433.

[11] Omar Banimelhem, Moad Mowafi, Eyad Taqieddin, Fahed Awad, Manar Al Rawabdeh, “An Efficient Clustering Approach using Genetic Algorithm and Node Mobility in Wireless Sensor Networks”, 11th International Symposium on Wireless Communications Systems (ISWCS), 2014, pp: 858 – 862.

[12] Ying Liang and Haibin Yu, “PSO-Based Energy Efficient Gathering in Sensor Networks”, International Conference on Mobile Ad-Hoc and Sensor Networks,2005, pp 362-369.

[13] Akyildiz IF, W. Su, Y. Sankarasubramaniam, Cayirci E. Wireless sensor networks: A survey. Computer Networks, vol. 38,no. 4, pp. 393–422, March 2002.

[14] Bandyopadhyay S, Coyle E. J. An energy efficient hierarchical clustering algorithm for wireless sensor networks. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM), 2003.

[15] Estrin D, Culler D, Pister K, Sukhatme G. Connecting the physical world with pervasive networks. IEEE Pervasive Computing, pages 59 – 69, January-March 2002.

[16] Heinzelman W. R, Chandrakasan A, Balakrishnan H. Energy-efficient communication protocol for wireless micro sensor networks. In Proceedings of the Hawaii International Conference on System Sciences, January 2000.

[17] Heinzelman W, Chandrakasan A.P, Balakrishnan H. An Application-Specific Protocol Architecture for Wireless Micro sensor Networks. IEEE Transaction on Wireless Communications, Vol. 1, No. 4, Oct. 2002.

[18] Hussain S, Matin AW. Base station assisted hierarchical cluster-based routing. in IEEE/ACM International Conference on Wireless and Mobile communications Networks(ICWMC), July 2006.

[19] Hussain S, Matin AW, Islam O. Genetic algorithm for energy efficient clusters in wireless sensor networks. in Fourth International Conference on Information Technology: New Generations (ITNG 2007), April 2007.

[20] D. Goldberg, B. Karp, Y. Ke, S. Nath, and S. Seshan, Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, 1989.

[21] Maraiya K, Kant K, Gupta N. Efficient Cluster Head Selection Scheme for Data Aggregation in Wireless Sensor Network. International Journal of Computer Applications, vol. 23, no. 9, June 2011.

[22] Indragandhi, V., Logesh, R., Subramaniyaswamy, V., Vijayakumar, V., Siarry, P., & Uden, L. (2018). Multi-objective optimization and energy management in renewable based AC/DC microgrid. Computers & Electrical Engineering.

[23] Subramaniyaswamy, V., Manogaran, G., Logesh, R., Vijayakumar, V., Chilamkurti, N., Malathi, D., & Senthilselvan, N. (2018). An ontology-driven personalized food recommendation in IoT-based healthcare system. The Journal of Supercomputing, 1-33.

[24] Arunkumar, S., Subramaniyaswamy, V., & Logesh, R. (2018). Hybrid Transform based Adaptive Steganography Scheme using Support Vector Machine for Cloud Storage. Cluster Computing.

[25] Indragandhi, V., Subramaniyaswamy, V., & Logesh, R. (2017). Resources, configurations, and soft computing techniques for power management and control of PV/wind hybrid system. Renewable and Sustainable Energy Reviews, 69, 129-143.

[26] Ravi, L., & Vairavasundaram, S. (2016). A collaborative location based travel recommendation system through enhanced rating prediction for the group of users. Computational intelligence and neuroscience, 2016, Article ID: 1291358.

[27] Logesh, R., Subramaniyaswamy, V., Malathi, D., Senthilselvan, N., Sasikumar, A., & Saravanan, P. (2017). Dynamic particle swarm optimization for personalized recommender system based on electroencephalography feedback. Biomedical Research, 28(13), 5646-5650.

[28] Arunkumar, S., Subramaniyaswamy, V., Karthikeyan, B., Saravanan, P., & Logesh, R. (2018). Meta-data based secret image sharing application for different sized biomedical images. Biomedical Research,29.

[29] Vairavasundaram, S., Varadharajan, V., Vairavasundaram, I., & Ravi, L. (2015). Data mining‐based tag recommendation system: an overview. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 5(3), 87-112.

[30] Logesh, R., Subramaniyaswamy, V., & Vijayakumar, V. (2018). A personalised travel recommender system utilising social network profile and accurate GPS data. Electronic Government, an International Journal, 14(1), 90-113.

[31] Vijayakumar, V., Subramaniyaswamy, V., Logesh, R., & Sivapathi, A. (2018). Effective Knowledge Based Recommeder System for Tailored Multiple Point of Interest Recommendation. International Journal of Web Portals.

[32] Subramaniyaswamy, V., Logesh, R., & Indragandhi, V. (2018). Intelligent sports commentary recommendation system for individual cricket players. International Journal of Advanced Intelligence Paradigms, 10(1-2), 103-117.

[33] Indragandhi, V., Subramaniyaswamy, V., & Logesh, R. (2017). Topological review and analysis of DC-DC boost converters. Journal of Engineering Science and Technology, 12 (6), 1541–1567.

[34] Saravanan, P., Arunkumar, S., Subramaniyaswamy, V., & Logesh, R. (2017). Enhanced web caching using bloom filter for local area networks. International Journal of Mechanical Engineering and Technology, 8(8), 211-217.

[35] Arunkumar, S., Subramaniyaswamy, V., Devika, R., & Logesh, R. (2017). Generating visually meaningful encrypted image using image splitting technique. International Journal of Mechanical Engineering and Technology, 8(8), 361–368.

[36] Subramaniyaswamy, V., Logesh, R., Chandrashekhar, M., Challa, A., & Vijayakumar, V. (2017). A personalised movie recommendation system based on collaborative filtering. International Journal of High Performance Computing and Networking, 10(1-2), 54-63.

[37] Senthilselvan, N., Udaya Sree, N., Medini, T., Subhakari Mounika, G., Subramaniyaswamy, V., Sivaramakrishnan, N., & Logesh, R. (2017). Keyword-aware recommender system based on user demographic attributes. International Journal of Mechanical Engineering and Technology, 8(8), 1466-1476.

[38] Subramaniyaswamy, V., Logesh, R., Vijayakumar, V., & Indragandhi, V. (2015). Automated Message Filtering System in Online Social Network. Procedia Computer Science, 50, 466-475.

[39] Subramaniyaswamy, V., Vijayakumar, V., Logesh, R., & Indragandhi, V. (2015). Unstructured data analysis on big data using map reduce. Procedia Computer Science, 50, 456-465.

[40] Subramaniyaswamy, V., Vijayakumar, V., Logesh, R., & Indragandhi, V. (2015). Intelligent travel recommendation system by mining attributes from community contributed photos. Procedia Computer Science, 50, 447-455.

[41] Vairavasundaram, S., & Logesh, R. (2017). Applying Semantic Relations for Automatic Topic Ontology Construction. Developments and Trends in Intelligent Technologies and Smart Systems, 48.

[42] Logesh, R., Subramaniyaswamy, V., Vijayakumar, V., Gao, X. Z., & Indragandhi, V. (2017). A hybrid quantum-induced swarm intelligence clustering for the urban trip recommendation in smart city. Future Generation Computer Systems, 83, 653-673.

[43] Subramaniyaswamy, V., & Logesh, R. (2017). Adaptive KNN based Recommender System through Mining of User Preferences. Wireless Personal Communications, 97(2), 2229-2247.

[44] Logesh, R., & Subramaniyaswamy, V. (2017). A Reliable Point of Interest Recommendation based on Trust Relevancy between Users. Wireless Personal Communications, 97(2), 2751-2780.

[45] Logesh, R., & Subramaniyaswamy, V. (2017). Learning Recency and Inferring Associations in Location Based Social Network for Emotion Induced Point-of-Interest Recommendation. Journal of Information Science & Engineering, 33(6), 1629–1647.

[46] Subramaniyaswamy, V., Logesh, R., Abejith, M., Umasankar, S., & Umamakeswari, A. (2017). Sentiment Analysis of Tweets for Estimating Criticality and Security of Events. Journal of Organizational and End User Computing (JOEUC), 29(4), 51-71.


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