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Data popularity and shortest-job-first scheduling of network transfers

机译:网络传输的数据流行度和最短工作

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This paper presents a strategy for scheduling transfers of data items from a single source to a single destination. We are motivated by the scenarios in which an author with limited connectivity relies on a remote publishing server for sharing data items with readers. Our strategy is based on the Shortest Job First (SJF) algorithm with the computational cost expressed in terms of the transfer time and the number of readers waiting for an item. We consider cases with static and dynamic popularity of items. We prove that our strategy is optimal in the static case. For the dynamic case, we use simulation results to demonstrate that our strategy results in lower average waiting time when compared to an SJF algorithm that bases its decision only on the expected transfer time or only on the popularity of a data item.
机译:本文介绍了将数据项从单个源调度到单个目的地的策略。我们的激励是通过有限连接的作者依赖于远程发布服务器的方案,以将数据项与读取器共享。我们的策略基于最短的作业第一(SJF)算法,以转移时间和等待物品的读取器数量表示的计算成本。我们考虑静态和动态普及物品的案例。我们证明我们的策略在静态案例中是最佳的。对于动态案例,我们使用模拟结果表明,与SJF算法相比,我们的策略导致较低的平均等待时间,该算法仅基于预期转移时间或仅基于数据项的普及。

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