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Dynamic Power-Aware Scheduling Algorithms for Real-Time Task Sets with Fault-Tolerance in Parallel and Distributed Computing Environment

机译:具有在并行和分布式计算环境中具有容错的实时任务集的动态功率感知调度算法

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At present, saving energy consumption of modern processors and fault tolerance become major concerns due to the fact that high power consumption increases heat dissipation, which leads to decreased reliability of systems. Similarly, the faults of running tasks also reduce the reliability of systems. The algorithms proposed in this paper are based on the policy of shortest-task-first and combined with other efficient techniques, such as shared slack reclamation and checkpoint. Consequently, not only real-time tasks can be completed before deadline, but also reduction of the global power consumption and fault-tolerance will be satisfied dynamically. In this paper, we present four algorithms to cope with scheduling independent task sets and task sets with precedence relationship in homogeneous and heterogeneous systems, respectively. Moreover, we present dynamic fault-tolerant algorithm. Compared to the efficient algorithms presented so far, our algorithms show lower communicational complexity and much better scheduling performance in terms of makespan and energy consumption.
机译:目前,由于高功耗增加了散热,节省现代处理器和容错能力的能耗成为主要问题,这导致系统的可靠性降低。同样,运行任务的故障也降低了系统的可靠性。本文提出的算法基于最短任务 - 首先和与其他有效技术相结合的策略,例如共享松弛填海和检查点。因此,不仅可以在截止日期之前完成实时任务,而且可以动态满足全球功耗和容错的降低。在本文中,我们分别展示了四种算法来应对调度独立任务集和任务集,分别具有均匀和异构系统中的优先关系。此外,我们呈现了动态容错算法。与迄今为止所呈现的有效算法相比,我们的算法显示了较低的沟通复杂性,并在Mapespan和能量消耗方面更好的调度性能。

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