Hourly server workload forecasting up to 168 hours ahead using Seasonal ARIMA model

Data center workload prediction is important to take decisions in resources management system. Seasonal ARIMA model provide a good server workload methodology for the server workload forecasting. A large set of our experiments confirm that it has high performance, scalability and reliability and will bee integrated in our system. This paper presents a general expression in development of our forecast model in the project EnergeTic-FUI, France.