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Resource prediction based on double exponential smoothing in cloud computing

机译:云计算中基于双指数平滑的资源预测

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With the development of cloud computing, customers are more and more concerned with cost on the resources which are not free in the cloud. Cloud resource providers can offer users two payment plans, i.e., reservation and on-demand plans for resource provision. In general, cost on resources gained by reservation plan is cheaper than on-demand plan. So the accuracy of resource prediction is of importance. In this paper, we present a resource prediction model based on double exponential smoothing, which considers not only the current state of resources but also the history records. Experiments performed on CloudSim cloud simulator show that the proposed method has a better performance on prediction accuracy.
机译:随着云计算的发展,客户越来越关注那些在云中并非免费的资源的成本。云资源提供商可以为用户提供两种支付计划,即用于资源提供的预订和按需计划。通常,通过预订计划获得的资源成本要比按需计划便宜。因此,资源预测的准确性至关重要。在本文中,我们提出了一种基于双指数平滑的资源预测模型,该模型不仅考虑了资源的当前状态,还考虑了历史记录。在CloudSim云模拟器上进行的实验表明,该方法在预测精度上具有更好的性能。

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