Approximate throughput computation of stochastic marked graphs
A general iterative technique for approximate throughput computation of stochastic strongly connected marked graphs is presented. It generalizes a previous technique based on net decomposition through a single input-single output cut, allowing the split of the model through any cut. The approach has...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on software engineering 1994-07, Vol.20 (7), p.526-535 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 535 |
|---|---|
| container_issue | 7 |
| container_start_page | 526 |
| container_title | IEEE transactions on software engineering |
| container_volume | 20 |
| creator | Campos, J. Colom, J.M. Jungnitz, H. Silva, M. |
| description | A general iterative technique for approximate throughput computation of stochastic strongly connected marked graphs is presented. It generalizes a previous technique based on net decomposition through a single input-single output cut, allowing the split of the model through any cut. The approach has two basic foundations. First, a deep understanding of the qualitative behavior of marked graphs leads to a general decomposition technique. Second, after the decomposition phase, an iterative response time approximation method is applied for the computation of the throughput. Experimental results on several examples generally have an error of less than 3%. The state space is usually reduced by more than one order of magnitude; therefore, the analysis of otherwise intractable systems is possible.< > |
| doi_str_mv | 10.1109/32.297941 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_ieee_primary_297941</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>297941</ieee_id><sourcerecordid>28359503</sourcerecordid><originalsourceid>FETCH-LOGICAL-c333t-bbc72a8f9353776017bd66e056de92831b44a31afccdacdb242d9a9391e048d13</originalsourceid><addsrcrecordid>eNpdkEtLxDAUhYMoWEcXbl0VEcFFxzybZiMMgy8YcKPrkKbptGPb1CQF_fdGOszC1Vnc734cDgCXCC4RguKe4CUWXFB0BBIkiMgIw_AYJBCKImOsEKfgzPsdhJBxzhLwsBpHZ7_bXgWThsbZaduMU0i17WOo0NohtXXqg9WN8qHVaa_cp6nSrVNj48_BSa06by72uQAfT4_v65ds8_b8ul5tMk0ICVlZao5VUQvCCOc5RLys8txAlldG4IKgklJFkKq1rpSuSkxxJVSsjwykRYXIAtzO3lj2azI-yL712nSdGoydvIwOJhgkEbz-B-7s5IbYTSLBGBecwgjdzZB21ntnajm6uID7kQjKvxklwXKeMbI3e6HyWnW1U4Nu_eGBUCQELSJ2NWOtMeZw3Tt-AebueW0</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>195579740</pqid></control><display><type>article</type><title>Approximate throughput computation of stochastic marked graphs</title><source>IEEE Electronic Library (IEL)</source><creator>Campos, J. ; Colom, J.M. ; Jungnitz, H. ; Silva, M.</creator><creatorcontrib>Campos, J. ; Colom, J.M. ; Jungnitz, H. ; Silva, M.</creatorcontrib><description>A general iterative technique for approximate throughput computation of stochastic strongly connected marked graphs is presented. It generalizes a previous technique based on net decomposition through a single input-single output cut, allowing the split of the model through any cut. The approach has two basic foundations. First, a deep understanding of the qualitative behavior of marked graphs leads to a general decomposition technique. Second, after the decomposition phase, an iterative response time approximation method is applied for the computation of the throughput. Experimental results on several examples generally have an error of less than 3%. The state space is usually reduced by more than one order of magnitude; therefore, the analysis of otherwise intractable systems is possible.< ></description><identifier>ISSN: 0098-5589</identifier><identifier>EISSN: 1939-3520</identifier><identifier>DOI: 10.1109/32.297941</identifier><identifier>CODEN: IESEDJ</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Algorithms ; Applied sciences ; Approximation ; Approximation methods ; Computational modeling ; Computer science; control theory; systems ; Computer systems performance. Reliability ; Decomposition ; Delay ; Exact sciences and technology ; Iterative methods ; Performance analysis ; Proposals ; Queueing analysis ; Response time ; Software ; State-space methods ; Stochastic processes ; Studies ; Systems development ; Techniques ; Throughput</subject><ispartof>IEEE transactions on software engineering, 1994-07, Vol.20 (7), p.526-535</ispartof><rights>1995 INIST-CNRS</rights><rights>Copyright Institute of Electrical and Electronics Engineers, Inc. (IEEE) Jul 1994</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c333t-bbc72a8f9353776017bd66e056de92831b44a31afccdacdb242d9a9391e048d13</citedby><cites>FETCH-LOGICAL-c333t-bbc72a8f9353776017bd66e056de92831b44a31afccdacdb242d9a9391e048d13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/297941$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27923,27924,54757</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/297941$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=3419948$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Campos, J.</creatorcontrib><creatorcontrib>Colom, J.M.</creatorcontrib><creatorcontrib>Jungnitz, H.</creatorcontrib><creatorcontrib>Silva, M.</creatorcontrib><title>Approximate throughput computation of stochastic marked graphs</title><title>IEEE transactions on software engineering</title><addtitle>TSE</addtitle><description>A general iterative technique for approximate throughput computation of stochastic strongly connected marked graphs is presented. It generalizes a previous technique based on net decomposition through a single input-single output cut, allowing the split of the model through any cut. The approach has two basic foundations. First, a deep understanding of the qualitative behavior of marked graphs leads to a general decomposition technique. Second, after the decomposition phase, an iterative response time approximation method is applied for the computation of the throughput. Experimental results on several examples generally have an error of less than 3%. The state space is usually reduced by more than one order of magnitude; therefore, the analysis of otherwise intractable systems is possible.< ></description><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Approximation</subject><subject>Approximation methods</subject><subject>Computational modeling</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems performance. Reliability</subject><subject>Decomposition</subject><subject>Delay</subject><subject>Exact sciences and technology</subject><subject>Iterative methods</subject><subject>Performance analysis</subject><subject>Proposals</subject><subject>Queueing analysis</subject><subject>Response time</subject><subject>Software</subject><subject>State-space methods</subject><subject>Stochastic processes</subject><subject>Studies</subject><subject>Systems development</subject><subject>Techniques</subject><subject>Throughput</subject><issn>0098-5589</issn><issn>1939-3520</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1994</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpdkEtLxDAUhYMoWEcXbl0VEcFFxzybZiMMgy8YcKPrkKbptGPb1CQF_fdGOszC1Vnc734cDgCXCC4RguKe4CUWXFB0BBIkiMgIw_AYJBCKImOsEKfgzPsdhJBxzhLwsBpHZ7_bXgWThsbZaduMU0i17WOo0NohtXXqg9WN8qHVaa_cp6nSrVNj48_BSa06by72uQAfT4_v65ds8_b8ul5tMk0ICVlZao5VUQvCCOc5RLys8txAlldG4IKgklJFkKq1rpSuSkxxJVSsjwykRYXIAtzO3lj2azI-yL712nSdGoydvIwOJhgkEbz-B-7s5IbYTSLBGBecwgjdzZB21ntnajm6uID7kQjKvxklwXKeMbI3e6HyWnW1U4Nu_eGBUCQELSJ2NWOtMeZw3Tt-AebueW0</recordid><startdate>19940701</startdate><enddate>19940701</enddate><creator>Campos, J.</creator><creator>Colom, J.M.</creator><creator>Jungnitz, H.</creator><creator>Silva, M.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>IEEE Computer Society</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88E</scope><scope>88F</scope><scope>88I</scope><scope>88K</scope><scope>8AL</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>K9.</scope><scope>L.-</scope><scope>L6V</scope><scope>M0C</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M1Q</scope><scope>M2O</scope><scope>M2P</scope><scope>M2T</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>7SC</scope><scope>8FD</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>19940701</creationdate><title>Approximate throughput computation of stochastic marked graphs</title><author>Campos, J. ; Colom, J.M. ; Jungnitz, H. ; Silva, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c333t-bbc72a8f9353776017bd66e056de92831b44a31afccdacdb242d9a9391e048d13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1994</creationdate><topic>Algorithms</topic><topic>Applied sciences</topic><topic>Approximation</topic><topic>Approximation methods</topic><topic>Computational modeling</topic><topic>Computer science; control theory; systems</topic><topic>Computer systems performance. Reliability</topic><topic>Decomposition</topic><topic>Delay</topic><topic>Exact sciences and technology</topic><topic>Iterative methods</topic><topic>Performance analysis</topic><topic>Proposals</topic><topic>Queueing analysis</topic><topic>Response time</topic><topic>Software</topic><topic>State-space methods</topic><topic>Stochastic processes</topic><topic>Studies</topic><topic>Systems development</topic><topic>Techniques</topic><topic>Throughput</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Campos, J.</creatorcontrib><creatorcontrib>Colom, J.M.</creatorcontrib><creatorcontrib>Jungnitz, H.</creatorcontrib><creatorcontrib>Silva, M.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Military Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>Telecommunications (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Military Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Telecommunications Database</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on software engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Campos, J.</au><au>Colom, J.M.</au><au>Jungnitz, H.</au><au>Silva, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Approximate throughput computation of stochastic marked graphs</atitle><jtitle>IEEE transactions on software engineering</jtitle><stitle>TSE</stitle><date>1994-07-01</date><risdate>1994</risdate><volume>20</volume><issue>7</issue><spage>526</spage><epage>535</epage><pages>526-535</pages><issn>0098-5589</issn><eissn>1939-3520</eissn><coden>IESEDJ</coden><abstract>A general iterative technique for approximate throughput computation of stochastic strongly connected marked graphs is presented. It generalizes a previous technique based on net decomposition through a single input-single output cut, allowing the split of the model through any cut. The approach has two basic foundations. First, a deep understanding of the qualitative behavior of marked graphs leads to a general decomposition technique. Second, after the decomposition phase, an iterative response time approximation method is applied for the computation of the throughput. Experimental results on several examples generally have an error of less than 3%. The state space is usually reduced by more than one order of magnitude; therefore, the analysis of otherwise intractable systems is possible.< ></abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/32.297941</doi><tpages>10</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 0098-5589 |
| ispartof | IEEE transactions on software engineering, 1994-07, Vol.20 (7), p.526-535 |
| issn | 0098-5589 1939-3520 |
| language | eng |
| recordid | cdi_ieee_primary_297941 |
| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms Applied sciences Approximation Approximation methods Computational modeling Computer science control theory systems Computer systems performance. Reliability Decomposition Delay Exact sciences and technology Iterative methods Performance analysis Proposals Queueing analysis Response time Software State-space methods Stochastic processes Studies Systems development Techniques Throughput |
| title | Approximate throughput computation of stochastic marked graphs |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T08%3A43%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Approximate%20throughput%20computation%20of%20stochastic%20marked%20graphs&rft.jtitle=IEEE%20transactions%20on%20software%20engineering&rft.au=Campos,%20J.&rft.date=1994-07-01&rft.volume=20&rft.issue=7&rft.spage=526&rft.epage=535&rft.pages=526-535&rft.issn=0098-5589&rft.eissn=1939-3520&rft.coden=IESEDJ&rft_id=info:doi/10.1109/32.297941&rft_dat=%3Cproquest_RIE%3E28359503%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=195579740&rft_id=info:pmid/&rft_ieee_id=297941&rfr_iscdi=true |