A flow-based prediction scheme to manage resources in enterprise data centers

CIT(2008)

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摘要
Virtualization is widely used to enhance the utilization of the resources in the enterprise data centers. Migration can solve the resource shortage problem of a physical machine in virtualized environment. If the future resource usage can be predicted, the resource can be managed more efficiently. Auto Regression prediction scheme is well-known for its simplicity and accuracy, but it requires complex coefficient calculations. It is known that workloads of enterprise data center tend to have a specific pattern. In this environment, simpler prediction technique can be used without loss of accuracy. This paper introduces a flow-based prediction scheme which forecasts future resource usage when the usage has a pattern. Through the performance evaluation, we show that the proposed scheme outperforms the AR prediction scheme in terms of accuracy and overheads.
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关键词
resource shortage problem,virtualization,enterprise data centers,flow-based prediction,auto regression prediction,future resource usage forecasting,virtual machines,resource allocation,autoregressive processes,resource management,prediction theory,business data processing,operating systems,probability,computer science,data center,auto regressive,engineering management,mathematical model,artificial neural networks,time series analysis,accuracy,application software,data engineering,virtual environment,regression analysis
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