Abstract
With the development of micro-electro-mechanical-system, energy harvesting (EH)-enabled sensor nodes may be used in many applications. WSNs without EH-enabled nodes still have limited applicability due to limited battery resources. The introduction of EH-enabled sensor nodes in the network increases costs and reduces performance due to environmental factors. We propose the clustering-based BAT algorithm for energy harvesting (CBA-EH) in IoT-enable wireless sensor networks to maximize the network performance. The Bat Optimization Algorithm is employed to optimize the fitness factors associated with CH selection. These factors include residual energy, intra-cluster distance, inter-cluster distance, and distance between EH-nodes and sink. The utilization of EH-enabled nodes enables us to effectively manage and minimize the network’s operational costs. The simulation results show that the suggested approach significantly improves network stability and operating time compared to current methods. In comparison to the GAOC protocol, simulation findings demonstrate that CBA-EH enhances stability, network lifetime, and throughput by 45%, 42.13%, and 48%, respectively.














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References
Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.
Hentati, A., Jaafar, W., Frigon, J. F., & Ajib, W. (2020). Analysis of the interdelivery time in IoT energy harvesting wireless sensor networks. IEEE Internet of Things Journal, 8(6), 4920–4930.
Badi, A., & Mahgoub, I. (2021). ReapIoT: Reliable, energy-aware network protocol for large-scale internet-of-things (IoT) applications. IEEE Internet of Things Journal, 8(17), 13582–13592.
Zhang, P., Xiao, G., & Tan, H. P. (2013). Clustering algorithms for maximizing the lifetime of wireless sensor networks with energy-harvesting sensors. Computer Networks, 57(14), 2689–2704.
Sahoo, B. M., Amgoth, T., & Pandey, H. M. (2020). Particle swarm optimization based energy efficient clustering and sink mobility in heterogeneous wireless sensor network. Ad Hoc Networks, 106, 102237.
Sahoo, B. M., Pandey, H. M., & Amgoth, T. (2022). A genetic algorithm inspired optimized cluster head selection method in wireless sensor networks. Swarm and Evolutionary Computation, 75, 101151.
Sahoo, B. M., Pandey, H. M., & Amgoth, T. (2021). GAPSO-H: A hybrid approach towards optimizing the cluster-based routing in wireless sensor network. Swarm and Evolutionary Computation, 60, 100772.
Verma, S., Sood, N., & Sharma, A. K. (2019). Genetic algorithm-based optimized cluster head selection for single and multiple data sinks in heterogeneous wireless sensor network. Applied Soft Computing, 85, 105788.
Nayyar, A., & Singh, R. (2017). Ant colony optimization (ACO) based routing protocols for wireless sensor networks (WSN): A survey. International Journal of Advanced Computer Science and Applications, 8(2), 148–155.
Tabibi, S., & Ghaffari, A. (2019). Energy-efficient routing mechanism for mobile sink in wireless sensor networks using particle swarm optimization algorithm. Wireless Personal Communications, 104, 199–216.
Sah, D. K., & Amgoth, T. (2020). A novel efficient clustering protocol for energy harvesting in wireless sensor networks. Wireless Networks, 26(6), 4723–4737.
Wang, T., Zhang, G., Yang, X., & Vajdi, A. (2018). Genetic algorithm for energy-efficient clustering and routing in wireless sensor networks. Journal of Systems and Software, 146, 196–214.
Gupta, P., Tripathi, S., Singh, S., & Gupta, V. S. (2023). MPPT-EPO optimized solar energy harvesting for maximizing the WSN lifetime. Peer-to-Peer Networking and Applications, 16(1), 347–357.
Lipare, A., Edla, D. R., & Dharavath, R. (2021). Energy efficient fuzzy clustering and routing using BAT algorithm. Wireless Networks, 27, 2813–2828.
Nandhini, P., & Suresh, A. (2021). Energy efficient cluster based routing protocol using charged system harmony search algorithm in WSN. Wireless Personal Communications, 121, 1457–1470.
Dhiman, G., & Kumar, V. (2017). Spotted hyena optimizer: A novel bio-inspired based metaheuristic technique for engineering applications. Advances in Engineering Software, 114, 48–70.
Ge, Y., Nan, Y., & Chen, Y. (2020). Maximizing information transmission for energy harvesting sensor networks by an uneven clustering protocol and energy management. KSII Transactions on Internet and Information Systems (TIIS), 14(4), 1419–1436.
Sahoo, B. M., Pandey, H. M., & Amgoth, T. (2021, January). A whale optimization (WOA): meta-heuristic based energy improvement clustering in wireless sensor networks. In 2021 11th international conference on cloud computing, data science and engineering (confluence) (pp. 649–654). IEEE.
Hu, J., Luo, J., Zheng, Y., & Li, K. (2018). Graphene-grid deployment in energy harvesting cooperative wireless sensor networks for green IoT. IEEE Transactions on Industrial Informatics, 15(3), 1820–1829.
Sharma, D., & Bhondekar, A. P. (2019). An improved cluster head selection in routing for solar energy-harvesting multi-heterogeneous wireless sensor networks. Wireless Personal Communications, 108(4), 2213–2228.
Tang, C., Tan, Q., Han, Y., An, W., Li, H., & Tang, H. (2016). An energy harvesting aware routing algorithm for hierarchical clustering wireless sensor networks. KSII Transactions on Internet and Information Systems, 10(2), 504–521.
Dong, Y., Wang, J., Shim, B., & Kim, D. I. (2016). DEARER: A distance-and-energy-aware routing with energy reservation for energy harvesting wireless sensor networks. IEEE Journal on Selected Areas in Communications, 34(12), 3798–3813.
Haq, I. U., Javaid, Q., Ullah, Z., Zaheer, Z., Raza, M., Khalid, M., & Khan, S. (2020). E2-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks. International Journal of Distributed Sensor Networks, 16(10), 1550147720968047.
Ren, Q., & Yao, G. (2019). An energy-efficient cluster head selection scheme for energy-harvesting wireless sensor networks. Sensors, 20(1), 187.
Bozorgi, S. M., Rostami, A. S., Hosseinabadi, A. A. R., & Balas, V. E. (2017). A new clustering protocol for energy harvesting-wireless sensor networks. Computers and Electrical Engineering, 64, 233–247.
Saeed, N., Celik, A., Al-Naffouri, T. Y., & Alouini, M. S. (2019). Localization of energy harvesting empowered underwater optical wireless sensor networks. IEEE Transactions on Wireless Communications, 18(5), 2652–2663.
Azarhava, H., & Niya, J. M. (2020). Energy efficient resource allocation in wireless energy harvesting sensor networks. IEEE Wireless Communications Letters, 9(7), 1000–1003.
Li, M., Liu, C., & Li, Q. (2020). Energy collaboration for non-homogeneous energy harvesting in cooperative wireless sensor networks. IEEE Access, 8, 27027–27037.
Gupta, S. S., & Mehta, N. B. (2018). Revisiting effectiveness of energy conserving opportunistic transmission schemes in energy harvesting wireless sensor networks. IEEE Transactions on Communications, 67(4), 2968–2980.
Deng, X., Guan, P., Hei, C., Li, F., Liu, J., & Xiong, N. (2021). An intelligent resource allocation scheme in energy harvesting cognitive wireless sensor networks. IEEE Transactions on Network Science and Engineering, 8(2), 1900–1912.
Karami, A., & Guerrero-Zapata, M. (2015). A fuzzy anomaly detection system based on hybrid PSO-Kmeans algorithm in content-centric networks. Neurocomputing, 149, 1253–1269.
Mittal, N., Singh, U., & Sohi, B. S. (2017). A novel energy efficient stable clustering approach for wireless sensor networks. Wireless Personal Communications, 95, 2947–2971.
Alghamdi, T. A. (2020). Energy efficient protocol in wireless sensor network: Optimized cluster head selection model. Telecommunication Systems, 74, 331–345.
Chaurasia, S., & Kumar, K. (2023). MOORP: Metaheuristic based optimized opportunistic routing protocol for wireless sensor network. Wireless Personal Communications, 132, 1241–1272.
Wang, H., Li, K., & Pedrycz, W. (2020). An elite hybrid metaheuristic optimization algorithm for maximizing wireless sensor networks lifetime with a sink node. IEEE Sensors Journal, 20(10), 5634–5649.
Al-Qamaji, A., & Atakan, B. (2022). Event distortion-based clustering algorithm for energy harvesting wireless sensor networks. Wireless Personal Communications, 123, 3823–3824.
Kathiroli, P., & Selvadurai, K. (2022). Energy efficient cluster head selection using improved Sparrow Search Algorithm in Wireless Sensor Networks. Journal of King Saud University-Computer and Information Sciences, 34(10), 8564–8575.
Sahoo, B. M., Amgoth, T., & Pandey, H. M. (2021). Enhancing the network performance of wireless sensor networks on meta-heuristic approach: Grey Wolf Optimization. In Applications of artificial intelligence and machine learning: Select proceedings of ICAAAIML 2020 (pp. 469–482). Springer.
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Biswa Mohan Sahoo concept, design, analysis, writing—original draft, writing—review and editing. Abadhan Saumya Sabyasachi concept, design, analysis, writing—original draft.
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Sahoo, B.M., Sabyasachi, A.S. A Metaheuristic Algorithm Based Clustering Protocol for Energy Harvesting in IoT-Enabled WSN. Wireless Pers Commun 136, 385–410 (2024). https://doi.org/10.1007/s11277-024-11270-5
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DOI: https://doi.org/10.1007/s11277-024-11270-5