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Coordinated rescheduling of Bag-of-Tasks for executions on multiple resource providers

机译:任务包的协调重新安排,以在多个资源提供者上执行

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Metaschedulers can distribute parts of a Bag-of-Tasks (BoT) application among various resource providers in order to speed up its execution. The expected completion time of the user application is then calculated based on the run-time estimates of all applications running and waiting for resources. However, because of inaccurate run time estimates, initial schedules are not those that provide users with the earliest completion time. These estimates increase the time distance between the first and last tasks of a BoT application, which increases average user response time, especially in multi-provider environments. This paper proposes a coordinated rescheduling algorithm to handle inaccurate run-time estimates when executing BoT applications in multi-provider environments. The coordinated rescheduling defines which tasks can have start time updated based on the expected completion time of the entire BoT application. We have also evaluated the impact of system-generated run-time estimates to schedule BoT applications on multiple providers. We performed experiments using simulations and a real distributed platform, Grid'5000. From our experiments, we obtained reductions of up to 5 and 10% for response time and slowdown metrics, respectively, by using coordinated rescheduling over a traditional rescheduling solution. Moreover, coordinated rescheduling requires little modification of existing scheduling systems. System-generated predictions, on the other hand, are more complex to be deployed and may not reduce response times as much as coordinated rescheduling.
机译:元计划程序可以在各种资源提供者之间分发任务袋(BoT)应用程序的一部分,以加快其执行速度。然后,基于所有正在运行并等待资源的应用程序的运行时估计值,计算用户应用程序的预期完成时间。但是,由于运行时间估计不准确,因此初始计划并不是那些为用户提供最早完成时间的计划。这些估计会增加BoT应用程序的第一个任务和最后一个任务之间的时间距离,这会增加平均用户响应时间,尤其是在多提供商环境中。本文提出了一种协调重调度算法,以在多提供商环境中执行BoT应用程序时处理不准确的运行时估计。协调的重新调度根据整个BoT应用程序的预期完成时间定义可以更新开始时间的任务。我们还评估了系统生成的运行时估计对计划BoT应用程序在多个提供商上的影响。我们使用模拟和真实的分布式平台Grid'5000进行了实验。从我们的实验中,通过在传统的重新计划解决方案上使用协调的重新计划,我们分别将响应时间和减速指标分别减少了5%和10%。此外,协调的重新调度几乎不需要修改现有的调度系统。另一方面,系统生成的预测部署起来更复杂,并且可能不会像协调重新安排那样减少响应时间。

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