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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Resource Availability Prediction in Distributed Systems: An Approach for Modeling Non-Stationary Transition Probabilities
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Resource Availability Prediction in Distributed Systems: An Approach for Modeling Non-Stationary Transition Probabilities

机译：分布式系统中的资源可用性预测：一种用于建模非平稳过渡概率的方法

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摘要

Large scale distributed systems employ thousands of resources which inevitably suffer from the unavailability issue. Serious side effects like unexpected delay or failure in the application execution are probable in case of such an issue. The imposed outcome might then be catastrophic consequences for real time applications or penalties for the service providers. Better prediction of the resource unavailability helps diminishing the undesired outcomes. This paper proposes a resource availability prediction algorithm for the mentioned goal. The resource availability variation is modeled as a stochastic process. By analyzing the availability information of NDU resources and both physical and virtual machines of the PlantLab, we found that the transition probabilities among the availability levels are non-stationary. To cope with this characteristic, we introduce Availability Transition Patterns (ATPs); the ATPs are dynamically constructed and the transitions between them are modeled by a Markov chain. The future ATP is then predicted based on the constructed Markov chain, according to which the resource availability-level is predicted. Experimental results confirm the efficiency of the proposed prediction algorithm.
机译：大型分布式系统使用了数千个资源，这些资源不可避免地会遭受不可用问题的困扰。在这种情况下，很可能会出现严重的副作用，例如意外延迟或应用程序执行失败。这样强加的结果可能会对实时应用造成灾难性后果，或者对服务提供商造成惩罚。更好地预测资源不可用性有助于减少不良结果。针对上述目标提出了一种资源可用性预测算法。资源可用性变化被建模为随机过程。通过分析NDU资源以及PlantLab的物理和虚拟机的可用性信息，我们发现可用性级别之间的转换概率是非平稳的。为了应对这一特性，我们引入了可用性转换模式（ATP）； ATP是动态构建的，并且它们之间的过渡通过马尔可夫链进行建模。然后基于构造的马尔可夫链预测未来的ATP，据此预测资源可用性级别。实验结果证实了所提预测算法的有效性。

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