Mapping mixed-criticality applications on multi-core architectures

A common trend in real-time embedded systems is to integrate multiple applications on a single platform. Such systems are known as mixed-criticality (MC) systems when the applications are characterized by different criticality levels. Nowadays, multicore platforms are promoted due to cost and performance benefits. However, certification of multicore MC systems is challenging as concurrently executed applications of different criticalities may block each other when accessing shared platform resources. Most of the existing research on multicore MC scheduling ignores the effects of resource sharing on the response times of applications. Recently, a MC scheduling strategy was proposed, which explicitly accounts for these effects. This paper discusses how to combine this policy with an optimization method for the partitioning of tasks to cores as well as the static mapping of memory blocks, i.e., task data and communication buffers, to the banks of a shared memory architecture. Optimization is performed at design time targeting at minimizing the worst-case response times of tasks and achieving efficient resource utilization. The proposed optimization method is evaluated using an industrial application.