Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources
A fork-join processing network is a queueing network in which tasks associated with a job can be processed simultaneously. Fork-join processing networks are prevalent in computer systems, healthcare, manufacturing, project management, justice system, etc. Unlike the conventional queueing networks, f...
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| creator | Ozkan, Erhun |
| description | A fork-join processing network is a queueing network in which tasks
associated with a job can be processed simultaneously. Fork-join processing
networks are prevalent in computer systems, healthcare, manufacturing, project
management, justice system, etc. Unlike the conventional queueing networks,
fork-join processing networks have synchronization constraints that arise due
to the parallel processing of tasks and can cause significant job delays. We
study scheduling control in fork-join processing networks with multiple job
types and parallel shared resources. Jobs arriving in the system fork into
arbitrary number of tasks, then those tasks are processed in parallel, and then
they join and leave the network. There are shared resources processing multiple
job types. We study the scheduling problem for those shared resources (that is,
which type of job to prioritize at any given time) and propose an
asymptotically optimal scheduling policy in diffusion scale. |
| doi_str_mv | 10.48550/arxiv.2002.01496 |
| format | Article |
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associated with a job can be processed simultaneously. Fork-join processing
networks are prevalent in computer systems, healthcare, manufacturing, project
management, justice system, etc. Unlike the conventional queueing networks,
fork-join processing networks have synchronization constraints that arise due
to the parallel processing of tasks and can cause significant job delays. We
study scheduling control in fork-join processing networks with multiple job
types and parallel shared resources. Jobs arriving in the system fork into
arbitrary number of tasks, then those tasks are processed in parallel, and then
they join and leave the network. There are shared resources processing multiple
job types. We study the scheduling problem for those shared resources (that is,
which type of job to prioritize at any given time) and propose an
asymptotically optimal scheduling policy in diffusion scale.</description><identifier>DOI: 10.48550/arxiv.2002.01496</identifier><language>eng</language><subject>Mathematics - Optimization and Control ; Mathematics - Probability</subject><creationdate>2020-02</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,777,882</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2002.01496$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2002.01496$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Ozkan, Erhun</creatorcontrib><title>Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources</title><description>A fork-join processing network is a queueing network in which tasks
associated with a job can be processed simultaneously. Fork-join processing
networks are prevalent in computer systems, healthcare, manufacturing, project
management, justice system, etc. Unlike the conventional queueing networks,
fork-join processing networks have synchronization constraints that arise due
to the parallel processing of tasks and can cause significant job delays. We
study scheduling control in fork-join processing networks with multiple job
types and parallel shared resources. Jobs arriving in the system fork into
arbitrary number of tasks, then those tasks are processed in parallel, and then
they join and leave the network. There are shared resources processing multiple
job types. We study the scheduling problem for those shared resources (that is,
which type of job to prioritize at any given time) and propose an
asymptotically optimal scheduling policy in diffusion scale.</description><subject>Mathematics - Optimization and Control</subject><subject>Mathematics - Probability</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz71OwzAUhmEvDKhwAUycG0hw7Py4I4ooULVQQWaik_iYWpg4slNK755SmD7pG17pYewq42muioLfYPi2X6ngXKQ8y-flOXur_TAF78AbWPjwkSy9HWATfE8x2uEdnmjaH_8IezttYb1zkx0dwdJ30BxGioCDhg0GdI4cvG4xkIYXin4XjokLdmbQRbr83xlrFndN_ZCsnu8f69tVgmVVJsqgkIWRgoSQGfWqEJUueJ5rWUlRZUaXc6lLMkZzhblC7HXXKeKVMch1Jmfs-i97ArZjsJ8YDu0vtD1B5Q8Nb08M</recordid><startdate>20200204</startdate><enddate>20200204</enddate><creator>Ozkan, Erhun</creator><scope>AKZ</scope><scope>GOX</scope></search><sort><creationdate>20200204</creationdate><title>Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources</title><author>Ozkan, Erhun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a676-8fa235f32e2231ec8527d5044d373271fd693d6effd08a48aacdbb8e07ffa0d13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Mathematics - Optimization and Control</topic><topic>Mathematics - Probability</topic><toplevel>online_resources</toplevel><creatorcontrib>Ozkan, Erhun</creatorcontrib><collection>arXiv Mathematics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ozkan, Erhun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources</atitle><date>2020-02-04</date><risdate>2020</risdate><abstract>A fork-join processing network is a queueing network in which tasks
associated with a job can be processed simultaneously. Fork-join processing
networks are prevalent in computer systems, healthcare, manufacturing, project
management, justice system, etc. Unlike the conventional queueing networks,
fork-join processing networks have synchronization constraints that arise due
to the parallel processing of tasks and can cause significant job delays. We
study scheduling control in fork-join processing networks with multiple job
types and parallel shared resources. Jobs arriving in the system fork into
arbitrary number of tasks, then those tasks are processed in parallel, and then
they join and leave the network. There are shared resources processing multiple
job types. We study the scheduling problem for those shared resources (that is,
which type of job to prioritize at any given time) and propose an
asymptotically optimal scheduling policy in diffusion scale.</abstract><doi>10.48550/arxiv.2002.01496</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Mathematics - Optimization and Control Mathematics - Probability |
| title | Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources |
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