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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Requirement-Aware Strategies with Arbitrary Processor Release Times for Scheduling Multiple Divisible Loads
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Requirement-Aware Strategies with Arbitrary Processor Release Times for Scheduling Multiple Divisible Loads

机译:具有任意处理器发布时间的需求感知策略,用于调度多个可分负载

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This paper investigates the problem of scheduling multiple divisible loads in networked computer systems with a particular emphasis in capturing two important real-life constraints, the arbitrary processor release times (or ready times) and heterogeneous processing requirements of different loads. We study two distinct cases of interest, static case, where processors' release times are predetermined and known, and dynamic case, where release times are unknown until processors are released. To address the two cases, we propose two novel scheduling strategies, referred to as Static Scheduling Strategy (SSS) and Dynamic Scheduling Strategy (DSS), respectively. In addition, we capture a task's processing requirements in our strategies, a unique feature that is applicable for handling loads on networks that run proprietary applications only on certain nodes. Thus, each task can only be processed by some certain nodes in our formulation. To handle the contention of multiple applications that have various processing requirements but share the same processing nodes, we propose an efficient load selection policy, referred to as Most Remaining Load First (MRF). We integrate MRF into SSS and DSS to address the problem of scheduling multiple divisible loads with arbitrary processor release times and heterogeneous requirements. We evaluate the strategies using extensive simulation experiments.
机译:本文研究了在联网的计算机系统中调度多个可分割负载的问题,尤其着重于捕获两个重要的实际约束,即任意负载的处理器释放时间(或就绪时间)和不同负载的异构处理要求。我们研究了两个有趣的案例:静态案例和处理器案例,其中动态案例是预先确定和已知的处理器释放时间,动态案例是在处理器释放之前未知的释放时间。为了解决这两种情况,我们提出了两种新颖的调度策略,分别称为静态调度策略(SSS)和动态调度策略(DSS)。另外,我们在策略中捕获了任务的处理需求,这是一项独特的功能,适用于处理仅在某些节点上运行专有应用程序的网络上的负载。因此,每个任务只能由我们公式中的某些特定节点来处理。为了处理具有不同处理要求但共享相同处理节点的多个应用程序的争用,我们提出了一种有效的负载选择策略,称为最剩余负载优先(MRF)。我们将MRF集成到SSS和DSS中,以解决在任意处理器释放时间和异构需求下调度多个可分割负载的问题。我们使用广泛的模拟实验评估策略。

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