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Configuring Cloud Admission Policies under Dynamic Demand

机译:在动态需求下配置云入场策略

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摘要

We consider the problem of admitting sets of, possibly heterogenous, virtual machines (VMs) with stochastic resource demands onto physical machines (PMs) in a Cloud environment. The objective is to achieve a specified quality-of-service related to the probability of resource over-utilization in an uncertain loading condition, while minimizing the rejection probability of VM requests. We introduce a method which relies on approximating the probability distribution of the total resource demand on PMs and estimating the probability of over-utilization. We compare our method to two simple admission policies: admission based on maximum demand and admission based on average demand. We investigate the efficiency of the results of using our method on a simulated Cloud environment where we analyze the effects of various parameters (commitment factor, coefficient of variation etc.) on the solution for highly variate demands.
机译:我们考虑在云环境中将随机资源的录取,可能是异因,虚拟机(VMS)的问题达到云环境(PMS)。目标是实现与不确定的负载条件中资源过度利用率的概率相关的特定课程,同时最小化VM请求的抑制概率。我们介绍一种依赖于近似于PMS总资源需求的概率分布的方法,并估算过度利用率的概率。我们将我们的方法与两项简单的入学政策进行比较:基于基于平均需求的最大需求和入学的入学。我们调查在模拟云环境上使用我们的方法的结果的效率,在那里我们分析各种参数(承诺因子,变化系数等)对高度变化需求的效果。

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