多作业类型并行共享资源Fork-Join加工网络的控制
Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources
摘要：
叉接处理网络是一种排队网络，其中与作业相关联的任务可以同时处理。Fork-join处理网络在计算机系统、医疗保健、制造业、项目管理、司法系统等中普遍存在。与传统的排队网络不同，fork-join处理网络具有由于任务的并行处理而产生的同步约束，并且可能导致显著的作业延迟。研究了具有多作业类型和并行共享资源的fork-join加工网络中的调度控制问题。到达系统的作业分成任意数量的任务，然后这些任务被并行处理，然后它们加入和离开网络。存在处理多种作业类型的共享资源。我们研究这些共享资源的调度问题（即，哪种类型的工作，优先在任何给定的时间），并提出了一个渐进的最优调度策略的扩散尺度。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
