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A probabilistic model for quantifying the resilience of networked systems
Citation
Queiroz, C and Garg, SK and Tari, Z, A probabilistic model for quantifying the resilience of networked systems, IBM Journal of Research and Development, 57, (5) pp. 3:1-3:9. ISSN 2151-8556 (2013) [Refereed Article]
Copyright Statement
Copyright 2013 by International Business Machines Corporation
DOI: doi:10.1147/JRD.2013.2259433
Abstract
Resilience is an important aspect of computing systems. Previous work on resilience has often focused on the design and architectural aspects of such systems, and not on the quantification of resilience. In addition, quantification is often restricted to a limited portion of the system. In networked systems, where multiple heterogeneous components interact in a complex manner, resilience quantification becomes a nontrivial problem. This paper proposes a model for quantifying resilience on the basis of the interdependencies of services and their adaptation. It combines performance and adaptability metrics to compute resilience of individual services that are then applied to a Markov network that computes the overall system resilience. The adaptation metric, here called adaptivity, computes how often the service adapts and evaluates the efficiency of such adaptations in terms of performance improvement. This paper also presents an evaluation that considers critical infrastructure systems.
Item Details
Item Type: | Refereed Article |
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Keywords: | adaptation models, computational modeling, Markov random fields, mathematical model, predictive models, resilience |
Research Division: | Information and Computing Sciences |
Research Group: | Distributed computing and systems software |
Research Field: | Distributed systems and algorithms |
Objective Division: | Information and Communication Services |
Objective Group: | Information systems, technologies and services |
Objective Field: | Information systems, technologies and services not elsewhere classified |
UTAS Author: | Garg, SK (Dr Saurabh Garg) |
ID Code: | 93815 |
Year Published: | 2013 |
Web of Science® Times Cited: | 13 |
Deposited By: | Information and Communication Technology |
Deposited On: | 2014-08-19 |
Last Modified: | 2018-02-28 |
Downloads: | 0 |
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