TCA: A Multi Constraint Real-Time Task Scheduling Algorithm for Heterogeneous Cloud Environment

Sampa Sahoo, S. Sahu, Tanmay Kumar Rath, B. Sahoo, A. K. Turuk
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引用次数: 1

Abstract

Cloud computing is an emerging computing paradigm, where cloud resources are available according to the pay-per-use pricing model and can be scaled dynamically depending on the application needs. Noticeably, many real-time applications that demand both time and functional correctness are moving to cloud. So, it requires efficient use of cloud resources to support applications need. In this context, task scheduling is a well-known technique to achieve the performance improvement of applications running in clouds. Again, execution time and execution cost play a vital role in deciding an appropriate VM for execution of a real-time task. In this paper, we formulate the real-time task scheduling problem as a multi-constraint optimization problem with time and cost constraint. Further, proposed a solution through time and cost-efficient best fit (TCA: BF) and first fit (TCA: FF) scheduling algorithms. Extensive simulation is performed to validate the superiority of the proposed approach compared to some existing ones.
面向异构云环境的多约束实时任务调度算法
云计算是一种新兴的计算范式,其中可以根据按使用付费的定价模型获得云资源,并且可以根据应用程序需求动态扩展。值得注意的是,许多对时间和功能正确性都有要求的实时应用程序正在向云迁移。因此,它需要有效地利用云资源来支持应用程序的需要。在这种情况下,任务调度是一种众所周知的技术,用于实现在云中运行的应用程序的性能改进。同样,执行时间和执行成本在决定执行实时任务的合适VM方面起着至关重要的作用。本文将实时任务调度问题表述为具有时间和成本约束的多约束优化问题。在此基础上,提出了采用最优拟合(TCA: BF)和最优拟合(TCA: FF)调度算法的解决方案。通过大量的仿真验证了该方法与现有方法的优越性。
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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