Task Mapping and Partition Allocation for Mixed-Criticality Real-Time Systems

In this paper we address the mapping of mixed-criticality hard real-time applications on distributed embedded architectures. We assume that the architecture provides both spatial and temporal partitioning, thus enforcing enough separation between applications. With temporal partitioning, each application runs in a separate partition, and each partition is allocated several time slots on the processors where the application is mapped. The sequence of time slots for all the applications on a processor are grouped within a Major Frame, which is repeated periodically. We assume that the applications are scheduled using static-cyclic scheduling. We are interested to determine the task mapping to processors, and the sequence and size of the time slots within the Major Frame on each processor, such that the applications are schedulable. We have proposed a Tabu Search-based approach to solve this optimization problem. The proposed algorithm has been evaluated using several synthetic and real-life benchmarks.