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Computing Low Latency Batches with Unreliable Workers in Volunteer Computing Environments

机译:在志愿计算环境中使用不可靠的工人来计算低延迟批次

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Internet based volunteer computing projects such as SETI@home are currently restricted to performing coarse grained, embarrassingly parallel master-worker style tasks. This is partly due to the “pull” nature of task distribution in volunteer computing environments, where workers request tasks from the master rather than the master assigning tasks to arbitrary workers. In this paper we propose algorithms for computing batches of medium grained tasks with deadlines in pull-style volunteer computing environments. We develop models of unreliable workers based on analysis of trace data from an actual volunteer computing project. These models are used to develop algorithms for task distribution in volunteer computing systems with a high probability of meeting batch deadlines. We develop algorithms for perfectly reliable workers, computation-reliable workers and unreliable workers. Finally, we demonstrate the effectiveness of the algorithms through simulations using traces from actual volunteer computing environments.
机译:目前,基于Internet的志愿者计算项目(例如SETI @ home)仅限于执行粗粒度,令人尴尬的并行主工作者风格的任务。这部分是由于在自愿计算环境中任务分配的“拉动”性质,在该环境中,工作人员从主服务器请求任务,而不是由主服务器向任意工作人员分配任务。在本文中,我们提出了用于在拉式志愿者计算环境中计算具有截止日期的中粒度任务批次的算法。我们基于对实际志愿者计算项目中的跟踪数据的分析,开发了不可靠工人的模型。这些模型用于开发在志愿者计算系统中任务分配的算法,很有可能满足批处理截止日期。我们为完全可靠的工人,计算可靠的工人和不可靠的工人开发算法。最后,我们通过使用来自实际志愿者计算环境的跟踪进行仿真来证明算法的有效性。

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