1. Green Web Services: Improving Energy Efficiency in Data Centers via Workload Predictions Massimiliano Menarini, Filippo Seracini, Xiang Zhang, Tajana Rosing, Ingolf Krüger GREENS 2013

2. Our Message: A Top-down Approach The application layer contains fundamental information on the execution of a workflow There are useful correlations between service calls that we can leverage to optimize the overall behavior of the system  Leverage that information to predict future levels of workload and proactively allocate resources

3. S.O.PR.A Methodology

4. Accuracy of the workload predictions ▫ A small standard deviation of the time dependency is key to save more energy Faced Issues

5. Open Questions for Further Discussion Cross-layer monitoring, modeling and prediction ▫ How the different layers (application, middleware, OS, VM, PM) affect resource usage? ▫ How can we model those layers and their interactions so to take into account also resource contention? ▫ How can we measure, and what to measure, at each layer without affecting performance?