Scheduling of stream-based real-time applications for heterogeneous systems

Designers of mobile devices face the challenge of providing the user with more processing power while increasing battery life. Heterogeneous systems offer some opportunities to solve this challenge. In an heterogeneous system, multiple classes of processors with dynamic voltage and frequency scaling functionality are embedded in the mobile device. With such a system it is possible to maximize performance while minimizing power consumption if tasks are mapped to the class of processors where they execute the most efficiently. In this paper, we study the scheduling of tasks in a real-time context on a heterogeneous system-on-chip that has dynamic voltage and frequency scaling functionality. We develop a heuristic scheduling algorithm which minimizes the energy while still meeting the deadline. We introduce the concept of cross-platform task heterogeneity and model sets of tasks to conduct extensive experiments. The experimental results 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 those of the optimal solution.