Scenario selectrion and prediction for DVS-aware scheduling of multimedia applications

Modern multimedia applications usually have real-time constraints and they are implemented using application-domain specific embedded processors. Dimensioning a system requires accurate estimations of resources needed by the applications. Overestimation leads to over-dimensioning. For a good resource estimation, all the cases in which an application can run must be considered. To avoid an explosion in the number of different cases, those that are similar with respect to required resources are combined into, so called application scenarios. This paper presents a methodology and a tool that can automatically detect the most important variables from an application and use them to select and dynamically predict scenarios, with respect to the necessary time budget, for soft real-time multimedia applications. The tool was tested for three multimedia applications. Using a proactive scenario-based dynamic voltage scheduler based on the scenarios and the runtime predictor generated by our tool, the energy consumption decreases with up to 19%, while guaranteeing a frame deadline miss ratio close to zero.