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Optimal Scheduling for Real-Time Jobs in Energy Harvesting Computing Systems

机译:能量收集计算系统中实时作业的最佳调度

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In this paper, we study a scheduling problem, in which every job is associated with a release time, deadline, required computation time, and required energy. We focus on an important special case where the jobs execute on a uniprocessor system that is supplied by a renewable energy source and use a rechargeable storage unit with limited capacity. Earliest deadline first (EDF) is a class one online algorithm in the classical real-time scheduling theory where energy constraints are not considered. We propose a semi-online EDF-based scheduling algorithm theoretically optimal (i.e., processing and energy costs neglected). This algorithm relies on the notions of energy demand and slack energy, which are different from the well known notions of processor demand and slack time. We provide an exact feasibility test. There are no restrictions on this new scheduler: each job can be one instance of a periodic, aperiodic, or sporadic task with deadline.
机译:在本文中,我们研究了一个调度问题,其中每个工作都与发布时间,截止日期,所需的计算时间和所需的能量相关联。我们关注一个重要的特殊情况,即作业在由可再生能源提供的单处理器系统上执行,并使用容量有限的可充电存储单元。最早截止时间优先(EDF)是经典实时调度理论中的一种在线算法,该算法不考虑能源约束。我们提出了一种基于半在线EDF的调度算法,该算法在理论上是最优的(即忽略了处理和能源成本)。该算法依赖于能量需求和松弛能量的概念,这与众所周知的处理器需求和松弛时间的概念不同。我们提供了确切的可行性测试。这项新的排程器没有任何限制:每个工作可以是有期限的周期性,非周期性或零星任务的一个实例。

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