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云环境下工作负载的预测方法

A Predictive Method for Workload Forecasting in the Cloud Environment

作者:Yao-Chung Chang;Ruay-Shiung Chang;Feng-Wei Chuang 作者单位:Department of Computer Science and Information Engineering, National Taitung University, Taitung, Taiwan, Republic of China 加工时间:2015-07-16 信息来源:科技报告(other) 索取原文[9 页]
关键词:节能;云计算;预测性工作负荷;神经网络
摘 要:In order to improve the performance and energy saving of the cloud computing, the efficiency of resource allocation has become an important issue. In this study, a neural network model with learning algorithm is applied to predict the workload of the cloud server. The resource manager deployed on the cloud server provides the service of managing the jobs with a resource allocation algorithm. With this prediction mechanism, cloud service providers can forecast the following time workload of cloud servers in advance. The experimental results show that resources can be allocated efficiently and become load balanced by proposed mechanism. Therefore, the cloud server can avoid the problem of inadequate resources.
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