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Cost-Minimizing Scheduling of Workflows on a Cloud of Memory Managed Multicore Machines

机译：在内存托管的多核计算机云上以最低成本调度工作流

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Workflows are modeled as hierarchically structured directed acyclic graphs in which vertices represent computational tasks, referred to as requests, and edges represent precedent constraints among requests. Associated with each workflow is a deadline that defines the time by which all computations of a workflow should be complete. Workflows are submitted by numerous clients to a scheduler that assigns workflow requests to a cloud of memory managed multicore machines for execution. A cost function is assumed to be associated with each workflow, which maps values of relative workflow tardiness to corresponding cost function values. A novel cost-minimizing scheduling framework is introduced to schedule requests of workflows so as to minimize the sum of cost function values for all workflows. The utility of the proposed scheduler is compared to another previously known scheduling policy.
机译：工作流被建模为分层结构的有向无环图，其中顶点表示计算任务（称为请求），边表示请求中的先行约束。与每个工作流程相关的是一个截止日期，该截止时间定义了完成工作流程所有计算的时间。许多客户端将工作流提交给调度程序，该调度程序将工作流请求分配给由内存管理的多核计算机组成的云以供执行。假定成本函数与每个工作流程相关联，每个工作流程将相对工作流程延迟的值映射到相应的成本函数值。引入了一种新颖的成本最小的调度框架来调度工作流的请求，以最小化所有工作流的成本函数值之和。将拟议的调度程序的效用与另一个先前已知的调度策略进行比较。

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