Multi-Population Ensemble Particle Swarm Optimizer based Energy Efficient Clustering Algorithms for IOT Applications
DOI:
https://doi.org/10.24113/ijoscience.v7i8.409Keywords:
Internet of Things (IoT), Wireless Sensor Network, Optimization, Energy Efficiency.Abstract
With the growth of wireless sensor networks (WSN), new technologies like the Internet-of-Things (IoT) are being created. There may be challenges that come because when implementing these application areas in practice. The primary issue is energy utilization while data transmission between these resource restricted sensors. In this work, we present a cluster-based routing protocol for IoT to anticipate energy utilization. Furthermore, for cluster head selection and cluster updation, we presented a multi-population ensemble particle swarm optimizer. The simulation was carried out using the MATLAB platform and demonstrates its superiority over different approaches.
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Ullah, I.; Youn, H. Y. Efficient Data Aggregation with Node Clustering and Extreme Learning Machine for WSN. J. Supercomput. 2020, 76 (12), 10009–10035. https://doi.org/10.1007/s11227-020-03236-8.
Radhika, S.; Rangarajan, P. On Improving the Lifespan of Wireless Sensor Networks with Fuzzy Based Clustering and Machine Learning Based Data Reduction. Appl. Soft Comput. J. 2019, 83, 105610. https://doi.org/10.1016/j.asoc.2019.105610.
Manzoor, K.; Jokhio, S. H.; Khanzada, T. J. S.; Jokhio, I. A. Enhanced TL-LEACH Routing Protocol for Large-Scale WSN Applications. In Proceedings - 2019 Cybersecurity and Cyberforensics Conference, CCC 2019; Institute of Electrical and Electronics Engineers Inc., 2019; pp 35–39. https://doi.org/10.1109/CCC.2019.00-12.
Banerjee, I.; Madhumathy, P. An Agent Cluster Based Routing Protocol for Enhancing Lifetime of Wireless Sensor Network. In 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing and Communication Engineering, ICATIECE 2019; Institute of Electrical and Electronics Engineers Inc., 2019; pp 265–268. https://doi.org/10.1109/ICATIECE45860.2019.9063788.
Behera, T. M.; Samal, U. C.; Mohapatra, S. K. Energy-Efficient Modified LEACH Protocol for IoT Application. IET Wirel. Sens. Syst. 2018, 8 (5), 223–228. https://doi.org/10.1049/iet-wss.2017.0099.
Razzaq, M.; Devi Ningombam, D.; Shin, S. Energy Efficient K-Means Clustering-Based Routing Protocol for WSN Using Optimal Packet Size. In International Conference on Information Networking; IEEE Computer Society, 2018; Vol. 2018-January, pp 632–635. https://doi.org/10.1109/ICOIN.2018.8343195.
Wibisono, W.; Ahmad, T.; Anggoro, R. Position-Based Scheme for Multi-Hop Routing Protocol in Cluster-Based Wireless Sensor Networks. In Proceeding of 2018 4th International Conference on Wireless and Telematics, ICWT 2018; Institute of Electrical and Electronics Engineers Inc., 2018. https://doi.org/10.1109/ICWT.2018.8527735.
Abidoye, A. P.; Obagbuwa, I. C. Models for Integrating Wireless Sensor Networks into the Internet of Things. IET Wirel. Sens. Syst. 2017, 7 (3), 65–72. https://doi.org/10.1049/iet-wss.2016.0049.
Wu, W.; Xiong, N.; Wu, C. Improved Clustering Algorithm Based on Energy Consumption in Wireless Sensor Networks. IET Networks 2017, 6 (3), 1–7. https://doi.org/10.1049/iet-net.2016.0115.
Li, P.; Jiang, W.; Xu, H.; Liu, W. Energy Optimization Algorithm of Wireless Sensor Networks Based on LEACH-B. In Lecture Notes on Data Engineering and Communications Technologies; Springer, 2017; Vol. 1, pp 391–404. https://doi.org/10.1007/978-3-319-49109-7_37.
N. Bilandi, H. K. Verma, and R. Dhir, “Performance and evaluation of energy optimization techniques for wireless body area networks,” Beni-Suef Univ. J. Basic Appl. Sci. 2020 91, vol. 9, no. 1, pp. 1–11, Sep. 2020, doi: 10.1186/S43088-020-00064-W.
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Copyright (c) 2021 Roshnee Adlak, Pooja Meena
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