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Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources

Erhun Özkan ()
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Erhun Özkan: College of Administrative Sciences and Economics, Koç University, Istanbul 34450, Turkey

Mathematics of Operations Research, 2022, vol. 47, issue 2, 1310-1334

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 systems, and so on. Unlike the conventional queueing networks, fork-join processing networks have synchronization constraints that arise because of the parallel processing of tasks and can cause significant job delays. We study scheduling 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 (i.e., which type of job to prioritize at any given time) and propose an asymptotically optimal scheduling policy in diffusion scale.

Keywords: 60K25; 90B22; 90B36; 93E20; 60F17; fork-join processing network; scheduling control; asymptotic optimality; diffusion scale (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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