论文标题
控制具有多种作业类型和并行共享资源的FORK-JOIN处理网络
Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources
论文作者
论文摘要
叉子加入处理网络是一个排队网络，可以同时处理与作业相关联的任务。在计算机系统，医疗保健，制造，项目管理，司法系统等中，叉子加入处理网络普遍存在。与常规排队网络不同，由于任务的并行处理而产生的同步约束，因此叉子加入的处理网络可能会导致任务的同步约束并可能导致重大工作差异。我们研究具有多种作业类型和并行共享资源的叉-Join处理网络中的调度控制。到达系统分叉的作业进入任意数量的任务，然后并行处理这些任务，然后加入并离开网络。共享资源处理多种作业类型。我们研究那些共享资源的调度问题（即，在任何给定时间要优先考虑哪种类型的工作），并在扩散量表中提出渐近最佳的调度策略。
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.
