Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources
| Autor: | Erhun Özkan |
|---|---|
| Přispěvatelé: | Özkan, Erhun (ORCID 0000-0001-6870-9495 & YÖK ID 294016), College of Administrative Sciences and Economics, Department of Business Administration |
| Rok vydání: | 2022 |
| Předmět: |
Queueing theory
60K25 90B22 90B36 93E20 60F17 business.industry General Mathematics Probability (math.PR) Control (management) Management Science and Operations Research Fork–join queue Operations research and management science Applied mathematics Fork-join processing network Scheduling control Asymptotic optimality Diffusion scale Computer Science Applications Optimization and Control (math.OC) FOS: Mathematics business Mathematics - Optimization and Control Mathematics - Probability Mathematics Computer network |
| Zdroj: | Mathematics of Operations Research |
| ISSN: | 1526-5471 0364-765X |
| DOI: | 10.1287/moor.2021.1170 |
| Popis: | 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. NA |
| Databáze: | OpenAIRE |
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