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首页> 外文期刊>Simulation modelling practice and theory: International journal of the Federation of European Simulation Societies >ALVEC: Auto-scaling by Lotka Volterra elastic cloud: A QoS aware non linear dynamical allocation model
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ALVEC: Auto-scaling by Lotka Volterra elastic cloud: A QoS aware non linear dynamical allocation model

机译:Alvec:Lotka Volterra Elastic云的自动缩放:QoS意识到非线性动态分配模型

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摘要

Measurement of the dynamic elasticity of resource allocation in cloud computing continues to be a relevant problem in the related literature. Yet, there is scant evidence on determining the dynamic scaling quotient in such operations. Elasticity is defined as the ability to adapt to the changing workloads by provisioning and de-provisioning of Cloud resources and scaling is essential for maintaining elasticity in resource allocation. We propose ALVEC, as a model of resource allocation in Cloud data centers (Sarkar et al., 2016) [7,16], to address dynamic allocation by auto-tuning the model parameters. The proposed model, governed by a coupled differential equation known as Lotka Volterra (LV), fares better for management of Service Level Agreement (SLA) and Quality of Services (QoS). We show evidence of true elasticity both in theoretical and numerical applications. Additionally, we show that ALVEC as an example of unsupervised resource allocation, is able to predict the future load and allocate virtual machines efficiently.
机译:测量云计算中资源分配的动态弹性仍然是相关文献中的相关问题。然而,有关于在这种操作中确定动态缩放商的许可证。弹性被定义为通过供应和解除云资源和缩放来适应变化工作负载的能力,并且缩放对于维持资源分配中的弹性至关重要。我们提出Alvec作为云数据中心的资源分配模式(Sarkar等,2016)[7,16],通过自动调整模型参数来解决动态分配。所提出的模型,由称为Lotka Volterra(LV)的耦合微分方程,对服务级别协议(SLA)和服务质量(QoS)提供更好的票价。我们展示了理论和数值应用中真正弹性的证据。此外,我们表明Alvec作为无监督的资源分配的示例,能够有效地预测未来的负载并分配虚拟机。

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