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Optimal and Event Driven Adaptive Fault Diagnosis for Arbitrary Network

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Advances in Computing and Data Sciences (ICACDS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1848))

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Abstract

Distributed computing system consists of numerous nodes that run as a single system. However, failures in nodes are unavoidable, which results in a node being marked as faulty. The system’s performance is impacted by these failures. So, fault diagnosis is a crucial part of the distributed computing system. This paper proposes a new algorithm called Optimal and Event Driven Adaptive Fault Diagnosis in Distributed System (OED-AFD) to identify faulty nodes in the system. This algorithm discovers the dynamic network along with detecting faulty nodes. The algorithm ensures that every node knows the status of all the nodes in the system at the end of every diagnostic cycle. The proposed algorithm is initiated either periodically or when an event, such as a new node entry or a repaired node re-entry is detected by the existing nodes of the system. The laboratory observations indicate that the proposed algorithm discovers and diagnoses any arbitrary distributed system using a minimal number of messages as compared to algorithms and methods proposed earlier by the authors.

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Authors and Affiliations

  1. MKSSS’s Cummins College of Engineering for Women, Department of Computer Engineering, Pune, India

    Pradnya Chaudhari, Anjusha Joshi, Supriya Kelkar, Anupama Joshi & Soniya Durgude

Authors
  1. Pradnya Chaudhari
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  2. Anjusha Joshi
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  3. Supriya Kelkar
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  4. Anupama Joshi
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  5. Soniya Durgude
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Corresponding author

Correspondence to Pradnya Chaudhari .

Editor information

Editors and Affiliations

  1. Consilio Research Lab, Tallinn, Estonia

    Mayank Singh

  2. Jaypee University of Engineering and Technology, Guna, India

    Vipin Tyagi

  3. Jaypee University of Information Technology, Waknaghat, India

    P.K. Gupta

  4. Institute of Information Theory and Automation, Prague, Czech Republic

    Jan Flusser

  5. University of Ottawa, Ottawa, ON, Canada

    Tuncer Ören

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Chaudhari, P., Joshi, A., Kelkar, S., Joshi, A., Durgude, S. (2023). Optimal and Event Driven Adaptive Fault Diagnosis for Arbitrary Network. In: Singh, M., Tyagi, V., Gupta, P., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2023. Communications in Computer and Information Science, vol 1848. Springer, Cham. https://doi.org/10.1007/978-3-031-37940-6_7

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  • DOI: https://doi.org/10.1007/978-3-031-37940-6_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-37939-0

  • Online ISBN: 978-3-031-37940-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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