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Minimizing Slowdown in Heterogeneous Size-Aware Dispatching Systems

机译:最小化异构大小感知调度系统中的速度降低

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We consider a system of parallel queues where tasks are assigned (dispatched) to one of the available servers upon arrival. The dispatching decision is based on the full state information, i.e., on the sizes of the new and existing jobs. We are interested in minimizing the so-called mean slowdown criterion corresponding to the mean of the sojourn time divided by the processing time. Assuming no new jobs arrive, the shortest-processing-time-produet (SPTP) schedule is known to minimize the slowdown of the existing jobs. The main contribution of this paper is three-fold: 1) To show the optimality of SPTP with respect to slowdown in a single server queue under Poisson arrivals; 2) to derive the so-called size-aware value functions for M/G/1-FIFO/LIFO/ SPTP with general holding costs of which the slowdown criterion is a special case; and 3) to utilize the value functions to derive efficient dispatching policies so as to minimize the mean slowdown in a heterogeneous server system. The derived policies offer a significantly better performance than e.g., the size-aware-task-assignment with equal load (SITA-E) and least-work-left (LWL) policies.
机译:我们考虑一个并行队列系统,该系统在到达时将任务分配(分派)给其中一个可用服务器。调度决策基于完整的状态信息,即基于新作业和现有作业的大小。我们感兴趣的是最小化所谓的平均减速标准,该标准对应于停留时间的平均值除以处理时间。假设没有新的作业到达,则已知最短处理时间(SPTP)计划可最大程度地减少现有作业的速度。本文的主要贡献是三个方面:1)证明在Poisson到达下单服务器队列中SPTP相对于速度下降的最优性; 2)推导具有一般持有成本的M / G / 1-FIFO / LIFO / SPTP的所谓的尺寸感知价值函数,其中减速准则是一种特殊情况; 3)利用价值函数得出有效的调度策略,以最大程度地降低异构服务器系统中的平均速度下降。派生的策略提供的性能要比例如等负载的大小感知任务分配(SITA-E)和最少工作量(LWL)策略好得多。

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