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The “Internet of Things (IoT) greatly depends on Wireless Sensor Networks (WSNs)”, which suffer huge issues with energy given the fact that sensor nodes cannot possess too much power. Clustering techniques help to minimize this by placing the nodes in groupings that consume less energy. However, much of the existing protocols fail to cluster efficiently or use energy comfortably. This study proposes a protocol that will extend the life of networks and their functionality, namely, the “Improved Energy-Efficient Clustering Protocol (IEECP)”. IEECP works by first determining the optimum number of balanced clusters, secondly by generating the clusters stagnately through an energy-balancing implementation of the “Fuzzy C Means algorithm and finally selection” of energy efficient cluster heads based on a new methodology known as selection-rotation. The performance is further improved by two major extensions: the extension 1 (extension 1) that introduces multipath routing to reduce the energy consumption and the quality of transmissions through main and minor channels. The "smaz-py3" library enables the compression of packets that consequently become smaller, occupy less bandwidth and can be transferred within less time with extension 2. Based on the results that were obtained using the conducted experiments, it is apparent that IEECP is a lot superior to traditional protocols in terms of “energy efficiency, network longitude, and latency”.
Keywords:
Wireless sensor network, Internet of Things, clustering protocol, energy consumption, network lifetime”.
Cite Article:
"An Improved Energy-Efficient Clustering Protocol to Prolong the Lifetime of the WSN-Based IoT", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 8, page no.a536-a540, August-2025, Available :http://www.ijrti.org/papers/IJRTI2508065.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator