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Cost-based Multi-QoS Job Scheduling Using Divisible Load Theory in Cloud Computing

机译:云计算中基于可分负载理论的基于成本的多QoS作业调度

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The advent of cloud computing as a new model of service provisioning in distributed systems, encourages researchers to investigate its benefits and drawbacks in executing scientific applications such as workflows. In this research, we attempt to investigate the use of a Divisible Load Theory (DLT) to design efficient strategies to minimize the overall processing time for scheduling jobs in compute cloud environments. We consider homogeneous processors in our analysis and we derive a closed-form solution for the load fractions to be assigned to each processors. Our analysis also attempts to schedule the jobs such a way that cloud provider can gain maximum benefit for his service and Quality of Service (QoS) requirement user's job. Finally, we quantify the performance of the strategies via rigorous simulation studies.
机译:云计算作为分布式系统中服务提供的新模型的出现,鼓励研究人员研究其在执行科学应用程序(例如工作流)中的利弊。在这项研究中,我们尝试研究使用可分负载理论(DLT)设计有效的策略,以最大程度地减少在计算云环境中调度作业的总体处理时间。我们在分析中考虑了同质处理器,并为要分配给每个处理器的负载分数导出了封闭形式的解决方案。我们的分析还尝试安排作业,以使云提供商可以从其服务和服务质量(QoS)要求用户的作业中获得最大收益。最后,我们通过严格的模拟研究来量化策略的性能。

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