首页> 外文期刊>Simulation modelling practice and theory: International journal of the Federation of European Simulation Societies >Performance evaluation of a SaaS cloud under different levels of workload computational demand variability and tardiness bounds
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Performance evaluation of a SaaS cloud under different levels of workload computational demand variability and tardiness bounds

机译:不同级别的工作量计算需求变异性和迟到界限的SaaS云的性能评估

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As the paradigm shift toward Software as a Service (SaaS) continues to gain momentum, there is a growing focus on the performance of SaaS clouds from both academia and industry. In this paper, we evaluate the performance of a SaaS cloud under various tardiness bounds and different levels of workload computational demand variability. The workload consists of bag-of-tasks jobs, which are scheduled on the underlying virtualized host environment. The jobs have soft deadlines and different levels of variability in their computational demands. A multi-tier SLA is employed, which imposes a soft and a hard tardiness bound on each job. Furthermore, the employed pricing scheme is based on the provided level of Quality of Service (QoS). The performance of the SaaS cloud is evaluated by simulation, in an attempt to shed light on how it is affected by the tardiness bound and the computational demand variability of the workload.
机译:随着作为服务(SaaS)作为软件的范式转移(SaaS)继续获得势头,越来越关注萨斯云从学术界和行业的表现。 在本文中,我们在各种迟到界限下评估了SaaS云的性能和不同的工作量计算需求变异性。 工作负载包括任务袋作业,这些作业计划于底层虚拟化主机环境上。 工作在其计算需求中具有柔软的截止日期和不同程度的可变性。 采用多层SLA,这在每份工作中都施加了柔软和困难的迟到。 此外,采用的定价方案基于提供的服务质量水平(QoS)。 通过仿真评估SaaS云的性能,试图阐明它如何如何受到迟到绑定的影响和工作量的计算需求变化。

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