Transient Reward Approximation for Continuous-Time Markov Chains

ISCAS OpenIR

	Transient Reward Approximation for Continuous-Time Markov Chains
	Hahn, EM; Hermanns, H; Wimmer, R; Becker, B
	2015
发表期刊	IEEE TRANSACTIONS ON RELIABILITY
ISSN	0018-9529
卷号	64 期号:4 页码:1254-1275
摘要	We are interested in the analysis of very large continuous-time Markov chains (CTMCs) with many distinct rates. Such models arise naturally in the context of reliability analysis, e.g., of computer network performability analysis, of power grids, of computer virus vulnerability, and in the study of crowd dynamics. We use abstraction techniques together with novel algorithms for the computation of bounds on the expected final and accumulated rewards in continuous-time Markov decision processes (CTMDPs). These ingredients are combined in a partly symbolic and partly explicit (symblicit) analysis approach. In particular, we circumvent the use of multi-terminal decision diagrams, because the latter do not work well if facing a large number of different rates. We demonstrate the practical applicability and efficiency of the approach on two case studies.; We are interested in the analysis of very large continuous-time Markov chains (CTMCs) with many distinct rates. Such models arise naturally in the context of reliability analysis, e.g., of computer network performability analysis, of power grids, of computer virus vulnerability, and in the study of crowd dynamics. We use abstraction techniques together with novel algorithms for the computation of bounds on the expected final and accumulated rewards in continuous-time Markov decision processes (CTMDPs). These ingredients are combined in a partly symbolic and partly explicit (symblicit) analysis approach. In particular, we circumvent the use of multi-terminal decision diagrams, because the latter do not work well if facing a large number of different rates. We demonstrate the practical applicability and efficiency of the approach on two case studies.
收录类别	SCI
关键词	Continuous-time Markov Chains Continuous-time Markov Decision Processes Abstraction Symbolic Methods Ordered Binary Decision Diagrams
部门归属	Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing, Peoples R China. Univ Saarland, D-66123 Saarbrucken, Germany. Univ Oxford, Oxford OX1 2JD, England. Univ Saarland, Dept Comp Sci, D-66123 Saarbrucken, Germany. Univ Freiburg, Breisgau, Germany. Univ Freiburg, Fac Engn, Chair Comp Architecture, Breisgau, Germany.
语种	英语
WOS记录号	WOS:000366323500012
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
内容类型	期刊论文
URI标识	http://ir.iscas.ac.cn/handle/311060/17427
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Hahn, EM,Hermanns, H,Wimmer, R,et al. Transient Reward Approximation for Continuous-Time Markov Chains[J]. IEEE TRANSACTIONS ON RELIABILITY,2015,64(4):1254-1275.
APA	Hahn, EM,Hermanns, H,Wimmer, R,&Becker, B.(2015).Transient Reward Approximation for Continuous-Time Markov Chains.IEEE TRANSACTIONS ON RELIABILITY,64(4),1254-1275.
MLA	Hahn, EM,et al."Transient Reward Approximation for Continuous-Time Markov Chains".IEEE TRANSACTIONS ON RELIABILITY 64.4(2015):1254-1275.

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