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An Online Cost-Based Job Scheduling Method by Cellular Automata in Cloud Computing Environment

机译:云计算环境中蜂窝自动机的基于在线成本的作业调度方法

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摘要

Cloud computing has expanded considerably in industry and research and is based on a pay-as-you-go payment model. In cloud computing environment, on one hand, jobs sent to the cloud to execution have a variety of attribute such as deadline, length, bandwidth requirements. On the other hand, various virtual machines have been created at different costs on existing physical resources. In this paper, a job scheduling method is proposed that carries out scheduling using cellular automata. The proposed algorithm is called CA-JS. The main goal of this method is to execute the jobs in the specified deadline and to increase the profitability of cloud providers. Also, in this paper, another attribute named hardness factor, is determined by each user of jobs sent to the cloud, which also specifies the running cost of jobs. The simulations carried out in the CloudSim environment indicate that the proposed method, in comparison with FCFS, Min-Min, and EDF algorithms, has better tardiness and makespan, and also, allows more jobs to be executed in their specified deadline.
机译:云计算在工业和研究中扩展了很大扩展,并基于支付支付的付款模式。在云计算环境中,一方面,发送到云执行的作业有各种属性,如截止日期,长度,带宽要求。另一方面,已经在现有物理资源上以不同的成本创建了各种虚拟机。在本文中,提出了一种使用蜂窝自动机进行调度的作业调度方法。该算法称为CA-JS。此方法的主要目标是在指定的截止日期中执行作业,并提高云提供商的盈利能力。此外,在本文中,另一个名为硬度因子的属性由发送到云的作业的每个用户确定,这也指定了作业的运行成本。 CloudSIM环境中执行的模拟表明,与FCF,MIN-MIN和EDF算法相比,该方法具有更好的迟到和Makespan,并且还允许在其指定的截止日期中执行更多的工作。

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