Scheduling of Stream-Based Real-Time Applications for Heterogeneous Systems

Recent mobile devices present the challenge of trying to offer both more and more processing power and increasing battery life to their users. Heterogenous systems offer opportunities to solve this challenge. In this thesis, we study the scheduling of tasks in a real-time context on a heterogeneous system-on-chip. We develop a heuristic scheduling algorithm which minimizes the energy while still meeting the deadline. We introduce the concept of task heterogeneity and model sets of tasks to conduct extensive experiments. These experiments show that our heuristic has a much higher success rate than existing state of the art heuristics and derives a solution whose energy requirements are close to the optimal solution