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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:并行和分布式计算环境中具有容错能力的实时任务集的动态Power-Aware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:当前,由于高功耗增加了散热,这导致系统可靠性降低,这一事实使得节省现代处理器的能耗和容错能力成为主要问题。同样,正在运行的任务的故障也会降低系统的可靠性。本文提出的算法基于最短任务优先的策略,并与其他有效技术相结合,例如共享松弛回收和检查点。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局功耗的降低和容错的要求。在本文中,我们提出了四种算法来分别处理同构和异构系统中的调度独立任务集和具有优先级关系的任务集。此外,我们提出了动态容错算法。与迄今提供的高效算法相比,我们的算法显示出较低的通信复杂性,并且在制造周期和能耗方面都具有更好的调度性能。

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