Abstract
Energy efficiency is a crucial factor in wireless sensor networks and helps in driving the network for long time. The basic approach to increase energy efficiency is routing through clustering. With this approach, many clusters of sensor nodes in the network region are formed, and a cluster head (CH) is selected for every cluster. This CH receives data packets from the cluster’s non-CH members and sends the data it has gathered to the base station (BS). But, after some transmissions, the CH can run out of energy. In this paper, we thus offer the Energy-efficient regression and Fuzzy based intelligent routing algorithm for Heterogeneous Wireless Sensor Network (HWSN). The Fine Cluster Head (FCH) has been chosen using the fuzzy inference system out of the selected CHs. Finally, the CH transfer the data gathered from the non-CH member to the chosen FCH. The hop-count from CHs to the FCH evaluated to build this effective route. Our simulation findings demonstrate that, in terms of Energy Efficiency, Packet Delivery Ratio, and Throughput, over without intelligence, and with regression models outperform the work currently being done.
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Mekala, S., Mallareddy, A., Tandu, R.R., Radhika, K. (2023). Machine Learning and Fuzzy Logic Based Intelligent Algorithm for Energy Efficient Routing in Wireless Sensor Networks. In: Morusupalli, R., Dandibhotla, T.S., Atluri, V.V., Windridge, D., Lingras, P., Komati, V.R. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2023. Lecture Notes in Computer Science(), vol 14078. Springer, Cham. https://doi.org/10.1007/978-3-031-36402-0_49
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