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Published:
May 2, 2026DOI:
10.4314/mejs.v18i1.3Keywords:
Article Details
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Main Article Content
Optimizing Wireless Sensor Networks Through Centrality Measures: A Case Study Using the Watts-Strogatz Model
Suneela Kallakunta
Sreenivas Alluri
Abstract
This study provides a comprehensive analysis of Wireless Sensor Networks (WSNs) by applying various centrality measures to identify key nodes within the network. The research focuses on a WSN comprising 100 nodes, modeled using the Watts-Strogatz model. This model effectively captures the network's structural properties, balancing randomness and regularity, which is crucial for understanding real-world WSNs. Degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, Katz centrality, subgraph centrality, and PageRank are utilized to assess individual nodes' relative importance and influence. The analysis highlights the structural significance of specific nodes, particularly those with high centrality scores, which are crucial in optimizing network performance, enhancing resilience, and improving resource management. The results underscore the utility of centrality measures and the Watts-Strogatz model in understanding network dynamics and designing strategies for network optimization, with Node 99 emerging as consistently central across all metrics. These findings have important implications for network management, particularly in applications requiring robust communication and efficient data processing.
