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An Adaptive Restart Mechanism for Continuous Epidemic Systems

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Internet and Distributed Computing Systems (IDCS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11874))

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Abstract

Software services based on large-scale distributed systems demand continuous and decentralised solutions for achieving system consistency and providing operational monitoring. Epidemic data aggregation algorithms provide decentralised, scalable and fault-tolerant solutions that can be used for system-wide tasks such as global state determination, monitoring and consensus. Existing continuous epidemic algorithms either periodically restart at fixed epochs or apply changes in the system state instantly producing less accurate approximation. This work introduces an innovative mechanism without fixed epochs that monitors the system state and restarts upon the detection of the system convergence or divergence. The mechanism makes correct aggregation with an approximation error as small as desired. The proposed solution is validated and analysed by means of simulations under static and dynamic network conditions.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Reading, Whiteknights, Reading, Berkshire, RG6 6AY, UK

    Mosab M. Ayiad & Giuseppe Di Fatta

Authors
  1. Mosab M. Ayiad
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  2. Giuseppe Di Fatta
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Corresponding author

Correspondence to Giuseppe Di Fatta .

Editor information

Editors and Affiliations

  1. Department of Science and Technology, Parthenope University of Naples, Napoli, Italy

    Raffaele Montella

  2. Parthenope University of Naples, Napoli, Italy

    Angelo Ciaramella

  3. University of Calabria, Rende, Italy

    Giancarlo Fortino

  4. ICAR, Consiglio Nazionale delle Ricerche, Rende, Cosenza, Italy

    Antonio Guerrieri

  5. Edinburgh Napier University, Edinburgh, UK

    Antonio Liotta

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Ayiad, M.M., Di Fatta, G. (2019). An Adaptive Restart Mechanism for Continuous Epidemic Systems. In: Montella, R., Ciaramella, A., Fortino, G., Guerrieri, A., Liotta, A. (eds) Internet and Distributed Computing Systems . IDCS 2019. Lecture Notes in Computer Science(), vol 11874. Springer, Cham. https://doi.org/10.1007/978-3-030-34914-1_6

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  • DOI: https://doi.org/10.1007/978-3-030-34914-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34913-4

  • Online ISBN: 978-3-030-34914-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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