Real-Time Scheduling of Reconfigurable Battery-Powered Multi-Core Platforms
Reconfigurable real-time embedded systems are constantly increasingly used in applications like autonomous robots or sensor networks. Since they are powered by batteries, these systems have to be energy-aware, to adapt to their environment and to satisfy real-time constraints. For energy harvesting systems, regular recharges of battery can be estimated, and by including this parameter in the operating system, it is then possible to develop strategy able to ensure the best execution of the application until the next recharge. In this context, operating system services must control the execution of tasks to meet the application constraints. Our objective concerns the proposition of a new real-time scheduling strategy that considers execution constraints such as the deadline of tasks and the energy for heterogeneous architectures. For such systems, we first addressed homogeneous architectures and extended our work for heterogeneous systems for which each task has different execution parameters. For these two architectures models, we formulated the problem as an ILP optimisation problem that can be solved by classical solvers. Assuming that the energy consumed by the communication is dependent on the distance between processors, we proposed a mapping strategy to minimise the total cost of communication between processors by placing the dependent tasks as close as possible to each other. The proposed strategy guarantees that, when a task is mapped into the system and accepted, it is then correctly executed prior to the task deadline. Finally, as on-line scheduling is targeted for this work, we proposed heuristics to solve these problems in efficient way. These heuristics are based on the previous packing strategy developed for the mono-processor architecture case.