Abstract
Resource administration is basically an important dire function in the data center that may be affect Service level agreement and operation cost provided by the data center known as OPEX and SLA. Efficient resource is the key factor of resource utilization and provided guarantee SLA to each application to maximize the resources in data center. Accurate prediction support each application in data center is the key requirement to provision an efficient resource management. However, Under-estimating and Overestimation in the application workload result shows the resource under provision or overestimating. In this paper, our approach to apply ARIMA model for workload applications in data center, it is forecasting technique and capture autocorrelation in the series by modeling it directly. The key concept of ARIMA model is ordering and differencing only with linear data capturing when data graph in straight line. We applies different operation model to fit applications workload time series. Performance of ARIMA can be tested by MATLAB simulation. We are using the ARIMA model parameters to find out prediction errors during the day and month calculated (i.e. Day = 7.01% and Month = 6.73%) to provide accuracy of ARIMA prediction model.
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