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Article type: Research Article
Authors: Ashok Kumar, M.a; * | Saravanan, K.b; *
Affiliations: [a] Department of Electronics and Communication Engineering, SCAD College of Engineering and Technology, Cheranmahadevi | [b] Department of Computer Science and Engineering, College of Engineering, Guindy, Anna University, Chennai
Correspondence: [*] Corresponding authors. M. Ashok Kumar, E-mail: ashokkumar65@yahoo.com and K. Saravanan, E-mail: saravanankrish@annauniv.edu.
Abstract: In multicasting packets of data from a node will be sent to a group of receiver nodes at the same time. Multicasting lowers transmission costs. Energy conservation is critical to a sensor network’s long-term viability. Sensor networks have limited and non-replenishable energy supplies, maximizing network lifetime is crucial in sensor nodes. As a result, clustering has become one of the popular methods for extending the lifetime of an entire system by integrating information at the cluster head. Cluster head (CH) selection is the important serving node in each cluster in the Wireless sensor networks (WSN). This paper introduces a High Power Node (HPN) multicasting approach which embeds a cluster of sink node data in packet headers to allow receiver for utilizing a approach for transferring multicast packet data via the shortest paths. The proposed Energy efficient multicasting cluster based routing (EEMCR) protocol utilized high power nodes, which shall play a critical role in minimal energy usage. The implementation findings demonstrate that, when compared with the previous methodologies, the suggested algorithm has enhanced in terms of packet delivery ratio (PDR), End to end delivery rate, efficiency and achieves low energy consumption. The proposed EEMCR obtain 95% efficiency. The results are then compared to other existing algorithms to determine the superiority of the proposed methodology.
Keywords: Routing, wireless sensor networks, multicasting, cluster head selection, clustering
DOI: 10.3233/JIFS-223536
Journal: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4753-4766, 2023
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