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Design of new scheduling algorithm LLF_DM and its comparison with existing EDF, LLF, and DM algorithms for periodic tasks

机译:新调度算法LLF_DM的设计及其与周期性任务的现有EDF,LLF和DM算法的比较

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The most challenging part of scheduling in real time systems is to achieve successful completion of a job before its deadline. Mainly two categories of algorithms i.e. static and dynamic tried to achieve this but both categories failed either in under-loaded condition or in over-loaded condition. Dynamic algorithms achieve optimum results in under-loaded condition but fail to achieve the same in over-loaded condition. On the other side static algorithms do not achieve optimum performance in underloaded condition but perform well in over-loaded condition. So our idea behind designing new scheduling algorithm is to achieve optimum performance in under-loaded condition and to achieve high performance in over-loaded condition. To achieve this we schedule jobs according to dynamic scheduling algorithm LLF (Least Laxity First) when system is under-loaded and when system becomes overloaded we schedule jobs according to static algorithm DM (Deadline Monotonic). In this paper we have proposed a LLF_DM algorithm which achieves optimum performance in under-loaded condition and achieves very high performance in over loaded condition.
机译:在实时系统中调度最具挑战性的部分是在截止日期之前成功完成工作。主要是两类算法I.E.静态和动态试图实现这一类别,但两类都失败了在负载不变的情况下或过加载的条件。动态算法实现了欠加载条件的最佳结果,但不能在过加载的情况下实现相同的情况。在另一侧静态算法上不会在未载荷的情况下实现最佳性能,但在过加载状态下表现良好。因此,我们的想法在设计新的调度算法背后是在负载不变状态下实现最佳性能,并在过加载状态下实现高性能。为了实现这一目标,我们根据系统未加载系统的动态调度算法LLF(最小松弛,当系统因静态算法DM(截止日期Monotonic)而过载时,当系统变得过载时,根据系统变得过载。在本文中,我们提出了一种LLF_DM算法,该算法在负载不变状态下实现了最佳性能,并在加载条件下实现了非常高的性能。

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