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Centralized and Distributed Approach: A Comparative Analysis of Fault Diagnosis Approaches in Wireless Sensor Networks
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Author(s): Dattatray G. Takale (Vishwakarma Institute of Information Technology, SPPU Pune, India), Parikshit N. Mahalle (Vishwakarma Institute of Technology, Pune, India)and Bipin Sule (Vishwakarma Institute of Information Technology, SPPU Pune, India)
Copyright: 2025
Pages: 22
Source title:
Machine Learning for Environmental Monitoring in Wireless Sensor Networks
Source Author(s)/Editor(s): Parikshit N. Mahalle (Department of Artificial Intelligence and Data Science, Vishwakarma Institute of Technology, Pune, India), Dattatray G. Takale (Vishwakarma Institute of Information Technology, India), Sachin Sakhare (Vishwakarma Institute of Information Technology, India)and Ganesh B. Regulwar (Vardhaman College of Engineering, India)
DOI: 10.4018/979-8-3693-3940-4.ch012
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Abstract
This Chapter presents a comparative analysis of two predominant fault diagnosis approaches, centralized and distributed, in WSNs. Fault diagnosis is paramount for maintaining network reliability and performance in diverse applications. Centralized fault diagnosis involves collecting and analyzing data at a central location, offering simplified management and efficient localization but potentially suffering from scalability issues. In contrast, distributed fault diagnosis leverages collaborative processing among sensor nodes, enhancing fault tolerance and scalability but requiring coordination and potentially incurring higher communication overhead. Factors such as network size, topology, resource constraints, and application requirements influence the choice between centralized and distributed approaches. This Chapter serves as a valuable resource for guiding decision-making processes and informing the selection of fault diagnosis methodologies in WSN deployments, contributing to the advancement of fault-tolerant and resilient wireless sensor networks.
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