Stochastic Model Checking with Stochastic Comparison
This paper presents a stochastic comparison based method to check state formulas defined over Discrete Time Markov Reward Models. High-level specifications like stochastic Petri nets, Stochastic Automata Networks, Stochastic Process Algebras have been developed to construct large Markov models. Howe...
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creator | Pekergin, Nihal Younès, Sana |
description | This paper presents a stochastic comparison based method to check state formulas defined over Discrete Time Markov Reward Models. High-level specifications like stochastic Petri nets, Stochastic Automata Networks, Stochastic Process Algebras have been developed to construct large Markov models. However computation of transient and steady-state distributions are limited to relatively small parameter sizes because of the state space explosion problem. Stochastic comparison technique by which both transient and steady-state bounding distributions can be computed, lets to overcome this problem. On the other hand, bounding techniques are useful in Model Checking, since we check generally formulas to see if they meet some bounds or not. We propose to apply stochastic bounding algorithms to construct bounding distributions and to check formulas through these distributions. |
doi_str_mv | 10.1007/11549970_9 |
format | Conference Proceeding |
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High-level specifications like stochastic Petri nets, Stochastic Automata Networks, Stochastic Process Algebras have been developed to construct large Markov models. However computation of transient and steady-state distributions are limited to relatively small parameter sizes because of the state space explosion problem. Stochastic comparison technique by which both transient and steady-state bounding distributions can be computed, lets to overcome this problem. On the other hand, bounding techniques are useful in Model Checking, since we check generally formulas to see if they meet some bounds or not. We propose to apply stochastic bounding algorithms to construct bounding distributions and to check formulas through these distributions.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 3540287019</identifier><identifier>ISBN: 9783540287018</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 9783540319030</identifier><identifier>EISBN: 3540319034</identifier><identifier>DOI: 10.1007/11549970_9</identifier><language>eng</language><publisher>Berlin, Heidelberg: Springer Berlin Heidelberg</publisher><subject>Applied sciences ; Atomic Proposition ; Computer science; control theory; systems ; Computer systems and distributed systems. User interface ; Computer systems performance. Reliability ; Discrete Time Markov Chain ; Exact sciences and technology ; Markov Chain ; Packet Loss ; Software ; State Formula</subject><ispartof>Formal Techniques for Computer Systems and Business Processes, 2005, p.109-123</ispartof><rights>Springer-Verlag Berlin Heidelberg 2005</rights><rights>2005 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/11549970_9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/11549970_9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>309,310,775,776,780,785,786,789,4035,4036,27904,38234,41421,42490</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17199057$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><contributor>Bravetti, Mario</contributor><contributor>Kloul, Leïla</contributor><contributor>Zavattaro, Gianluigi</contributor><creatorcontrib>Pekergin, Nihal</creatorcontrib><creatorcontrib>Younès, Sana</creatorcontrib><title>Stochastic Model Checking with Stochastic Comparison</title><title>Formal Techniques for Computer Systems and Business Processes</title><description>This paper presents a stochastic comparison based method to check state formulas defined over Discrete Time Markov Reward Models. High-level specifications like stochastic Petri nets, Stochastic Automata Networks, Stochastic Process Algebras have been developed to construct large Markov models. However computation of transient and steady-state distributions are limited to relatively small parameter sizes because of the state space explosion problem. Stochastic comparison technique by which both transient and steady-state bounding distributions can be computed, lets to overcome this problem. On the other hand, bounding techniques are useful in Model Checking, since we check generally formulas to see if they meet some bounds or not. We propose to apply stochastic bounding algorithms to construct bounding distributions and to check formulas through these distributions.</description><subject>Applied sciences</subject><subject>Atomic Proposition</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems and distributed systems. User interface</subject><subject>Computer systems performance. Reliability</subject><subject>Discrete Time Markov Chain</subject><subject>Exact sciences and technology</subject><subject>Markov Chain</subject><subject>Packet Loss</subject><subject>Software</subject><subject>State Formula</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>3540287019</isbn><isbn>9783540287018</isbn><isbn>9783540319030</isbn><isbn>3540319034</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNpNkE1LxDAYhOMXuK578Rf0Inipvm-SNnmPUtYPWPGgnkOapNu6u21pCuK_t8sKOpc5PMPADGNXCLcIoO4QM0mkwNARW5DSIpMgkEDAMZthjpgKIemEXewB1wqQTtlswjwlJcU5W8T4CZMEKsX1jMm3sXO1jWPjkpfOh21S1MFtmnadfDVjnfzDRbfr7dDErr1kZ5XdxrD49Tn7eFi-F0_p6vXxubhfpT1HPaacKq5zXwpATip477yyIvMyWFlRCAFCTiLPtfQhr0B4lBZKV00Trc6kFXN2fejtbXR2Ww22dU00_dDs7PBtUCERZGrK3RxycULtOgym7LpNNAhm_5r5e038AC7lWQ0</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Pekergin, Nihal</creator><creator>Younès, Sana</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope></search><sort><creationdate>2005</creationdate><title>Stochastic Model Checking with Stochastic Comparison</title><author>Pekergin, Nihal ; Younès, Sana</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p218t-29f286db301297eddcd7a35d4ea4f9eee0e6936684de6f03d14a0bcf549a854a3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Applied sciences</topic><topic>Atomic Proposition</topic><topic>Computer science; control theory; systems</topic><topic>Computer systems and distributed systems. User interface</topic><topic>Computer systems performance. Reliability</topic><topic>Discrete Time Markov Chain</topic><topic>Exact sciences and technology</topic><topic>Markov Chain</topic><topic>Packet Loss</topic><topic>Software</topic><topic>State Formula</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pekergin, Nihal</creatorcontrib><creatorcontrib>Younès, Sana</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pekergin, Nihal</au><au>Younès, Sana</au><au>Bravetti, Mario</au><au>Kloul, Leïla</au><au>Zavattaro, Gianluigi</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Stochastic Model Checking with Stochastic Comparison</atitle><btitle>Formal Techniques for Computer Systems and Business Processes</btitle><date>2005</date><risdate>2005</risdate><spage>109</spage><epage>123</epage><pages>109-123</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>3540287019</isbn><isbn>9783540287018</isbn><eisbn>9783540319030</eisbn><eisbn>3540319034</eisbn><abstract>This paper presents a stochastic comparison based method to check state formulas defined over Discrete Time Markov Reward Models. High-level specifications like stochastic Petri nets, Stochastic Automata Networks, Stochastic Process Algebras have been developed to construct large Markov models. However computation of transient and steady-state distributions are limited to relatively small parameter sizes because of the state space explosion problem. Stochastic comparison technique by which both transient and steady-state bounding distributions can be computed, lets to overcome this problem. On the other hand, bounding techniques are useful in Model Checking, since we check generally formulas to see if they meet some bounds or not. We propose to apply stochastic bounding algorithms to construct bounding distributions and to check formulas through these distributions.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/11549970_9</doi><tpages>15</tpages></addata></record> |
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language | eng |
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source | Springer Books |
subjects | Applied sciences Atomic Proposition Computer science control theory systems Computer systems and distributed systems. User interface Computer systems performance. Reliability Discrete Time Markov Chain Exact sciences and technology Markov Chain Packet Loss Software State Formula |
title | Stochastic Model Checking with Stochastic Comparison |
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