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

V. Prajapati, Apurva Shah, Prem Balani
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引用次数: 6

Abstract

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.
设计新的周期任务调度算法LLF_DM,并与现有的EDF、LLF和DM算法进行比较
实时系统调度中最具挑战性的部分是在截止日期之前成功完成任务。主要有两类算法,即静态和动态,试图实现这一点,但这两类算法在负载不足或过载的情况下都失败了。动态算法在欠载情况下能达到最优效果,而在过载情况下不能达到最优效果。另一方面,静态算法在欠载情况下不能达到最佳性能,但在过载情况下表现良好。因此,我们设计新的调度算法的思想是在低负载条件下实现最优性能,在过载条件下实现高性能。为了实现这一目标,我们在系统负载不足时根据动态调度算法LLF (Least Laxity First)调度作业,当系统过载时根据静态调度算法DM (Deadline Monotonic)调度作业。在本文中,我们提出了一种LLF_DM算法,该算法在低负载条件下达到最佳性能,在过载条件下达到非常高的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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