Abstract | ||
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Resiliency (resilience) is one of the important criteria for evaluating the sturdiness of systems. The resiliency is generally defined as the ability of resistance from disturbance that is caused by sudden changes of system configuration. However, there is no formal quantitative definition of system resiliency. In this paper, we propose the quantification of system resiliency by using continuous time Markov chains (CTMCs). According to probabilistic models, we formulate the quantification resiliency for performance indices of the system by two methods. Also, we discuss the applicability of our quantification of resiliency and compare the effectiveness of two definitions through numerical examples. |
Year | DOI | Venue |
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2013 | 10.1109/ISSREW.2013.6688852 | ISSRE (Supplemental Proceedings) |
Keywords | Field | DocType |
probabilistic models,ctmc,software reliability,markov reward process,characteristic analysis,continuous time markov chains,performance evaluation,system resiliency measure,markov processes,system resiliency | Psychological resilience,Markov process,Computer science,Markov model,Markov chain,Real-time computing,Variable-order Markov model,Probabilistic logic,Software quality,Reliability engineering,Markov renewal process | Conference |
Citations | PageRank | References |
1 | 0.42 | 3 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
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Chao Luo | 1 | 58 | 17.22 |
Hiroyuki Okamura | 2 | 145 | 24.45 |
Tadashi Dohi | 3 | 970 | 109.25 |