Regular Composite Resource Partition in Open Systems

Wei-Ju Chen, Pei-Chi Huang, Quan Leng, A. Mok, Song Han
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引用次数: 6

Abstract

In open systems, no global scheduler has knowledge of the complete resource requirements from all the applications. Each application has its own task group and can generate tasks on demand at run time. Regularity-based Resource Partition (RRP) model is an effective strategy to hierarchically allocate resource in such environments. However, when applying the RRP model to multi-resource environments, end-to-end tasks could experience unexpected delay and miss the deadlines. The tasks might arrive at non-resource-slice boundaries because the resource slice sizes of different physical resource may vary in such non-uniform environments. This paper extends the RRP model to non-uniform multi-resource open systems. It introduces a novel composite resource partition abstraction, identifies the feasible conditions for hierarchical regular composite resource partitioning and proposes an acyclic regular composite resource partition scheduling (ARCRPS) algorithm. Simulation results show that compared with the state-of-the-art approach, ARCRPS improves the acceptance ratio by 20% and 25% in uniform and non-uniform multi-resource environments, respectively. A multi-resource scheduling framework jointly considering the CPU and network resources is also designed and implemented to evaluate the feasibility of this theoretical model in practice.
开放系统中的规则组合资源分区
在开放系统中,没有全局调度器了解所有应用程序的完整资源需求。每个应用程序都有自己的任务组,可以在运行时按需生成任务。基于规则的资源划分(RRP)模型是在这种环境下进行资源分层分配的有效策略。然而,当将RRP模型应用于多资源环境时,端到端任务可能会遇到意想不到的延迟并错过截止日期。任务可能到达非资源片边界,因为在这种不统一的环境中,不同物理资源的资源片大小可能不同。本文将RRP模型扩展到非统一的多资源开放系统。引入了一种新的组合资源分区抽象,确定了分层规则组合资源分区的可行条件,提出了一种非循环规则组合资源分区调度算法。仿真结果表明,在均匀多资源环境和非均匀多资源环境下,ARCRPS算法的接收率分别提高了20%和25%。设计并实现了一个综合考虑CPU和网络资源的多资源调度框架,以评估该理论模型在实际应用中的可行性。
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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