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Time/utility function decomposition techniques for utility accrual scheduling algorithms in real-time distributed systems

机译:实时分布式系统中效用应计调度算法的时间/效用函数分解技术

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We consider Real-Time CORBA 1.2's distributable threads (DTs), whose time constraints are specified using time/utility functions (TUFs), operating in legacy environments. In legacy environments, system node resources - both physical and logical - are shared among time-critical DTs and local applications that may also be time-critical. Hence, DTs that are scheduled using their propagated TUFs, as mandated by Real-Time CORBA 1.2's Case 2 approach, may suffer performance degradation, if a node utility accrual (UA) scheduler achieves higher locally accrued utility by giving higher eligibility to local threads than to DTs. To alleviate this, we consider decomposing TUFs of DTs into "sub-TUFs" for scheduling segments of DTs. We present five decomposition techniques, called UT, SCEQF, SCALL, OPTCON, and TUFS, which are specific to different classes of UA scheduling algorithms, such as those that use utility density and those that use deadline as their key decision metric. Our experimental studies identify the decomposition technique that performs best for each class of UA scheduling algorithms. In particular, our studies show that OPTCON and TUFS perform best for utility density-based UA algorithms, while SCEQF and SCALL perform best for deadline-based UA algorithms.
机译:我们考虑了实时CORBA 1.2的可分发线程(DT),它们的时间限制是使用时间/效用函数(TUF)指定的,并且在旧版环境中运行。在旧版环境中,系统节点资源(包括物理资源和逻辑资源)在时间紧迫的DT和可能也是时间紧迫的本地应用程序之间共享。因此,如果节点实用程序累计(UA)调度程序通过赋予本地更高的资格来实现更高的本地累计效用,则按照实时CORBA 1.2的案例2方法的要求,使用其传播的TUF进行调度的DT可能会遭受性能下降。线程而不是DT。为了减轻这种情况,我们考虑将DT的TUF分解为“ sub-TUF”,以调度DT的段。我们介绍了五种分解技术,分别称为UT,SCEQF,SCALL,OPTCON和TUFS,它们分别针对不同类别的UA调度算法,例如使用效用密度的算法和使用截止日期作为关键决策指标的算法。我们的实验研究确定了对于UA调度算法的每类都表现最佳的分解技术。特别是,我们的研究表明,OPTCON和TUFS在基于效用密度的UA算法中表现最佳,而SCEQF和SCALL在基于截止日期的UA算法中表现最好。

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