| The impact of Integrating K-Means, Mean-Shift and Centrality Clustering with Leach-C on Wireless Sensor Network Lifetime |
| Paper ID : 1014-ICCITS (R1) |
| Authors |
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Imane A Saroit *1, Dina Tarek Mohamed2 1Professor. Faculty of Computers and Artificial Intelligence. Cairo University. 25 AHMED ZEWAIL STREET, ORMAN |
| Abstract |
| Wireless Sensor Networks (WSNs) are made up of sensor nodes distributed across a given area to independently monitor environmental factors like temperature, humidity, pressure and motion. These nodes communicate wirelessly, they work together to send the gathered data to a central base station. The limited battery life of sensor nodes poses a significant challenge, making energy efficiency a critical point in WSN design. Extending network lifetime while maintaining reliable data transmission is essential for the success of WSN applications. Clustering is a widely used technique to enhance energy efficiency by organizing sensor nodes into groups, each managed by a Cluster Head (CH). The CHs then aggregate and transmit the data to the base station, reducing redundant transmissions and optimizing energy consumption. LEACH is the most famous hierarchical clustering-based distributed routing protocol designed for WSNs, may enhancements on LEACH have been proposed to improve its performance. LEACH-C suggested that the base station forms the clusters based on the nodes’ energy and location. This paper suggests integrating Leach-C protocol with one of three famous clustering methods; K-means, Mean-Shift and Closeness Centrality. It then measures the impact of using each of them in improving the energy efficiency and the network lifetime. A detailed simulation program for the integrated Leach-C was developed to analyze the impact of these clustering techniques under different data rates and nodes’ distributions. The results indicate that integrated Leach-C with K-means clustering outperforms the other two methods in terms of energy efficiency, leading to an extended network lifetime. |
| Keywords |
| Wireless Sensor Networks (WSNs), Energy Efficiency, Network Lifetime, K-means Clustering, Mean-Shift Clustering, Closeness Centrality |
| Status: Accepted (Oral Presentation) |