Centrality-Based Optimization of a 100-Node Wireless Sensor Network: A Random Walk Model Study

Sreenivas  Alluri; Kairavadi Suresh  Babu; Suneela Kallakunta

doi:10.5269/bspm.79385

Sreenivas Alluri Department of Electrical, Electronics and Communication Engineering, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India
Kairavadi Suresh Babu
Suneela Kallakunta Department of Electrical, Electronics and Communication Engineering, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India

Resumen

This paper aims to refine a specific random walk model of a Wireless Sensor Network (WSN) with a hundred nodes. The optimisation approach uses six centrality measures: degree, betweenness, closeness, eigenvector, Katz, and subgraph centrality, to rank and select nodes to improve communication efficiency, network survivability, and network optimisation. A set of algorithms that determine the importance of a node, known as centrality, is utilized. This study focuses on improving WSN performance by using centrality measures that help in node prioritization. There are also other benefits worth mentioning. Optimizations done at the node level can help yield good traffic flows, as well as network connectivity and network survivability. In addition, our research shows the effect of using centrality in node optimization on scaling and reliability problems that WSNs usually have. The proposed optimization method enhances the WSN functionality, and at the same time, makes important nodes visible and reachable, thus solving a problem that has both academic and industrial relevance

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