Hard Real-Time Scheduling of Streaming Applications Modeled as Cyclic CSDF Graphs

Recently, it has been shown that the classical hard real-time scheduling theory can be applied to streaming applications modeled as acyclic Cyclo-Static Dataflow (CSDF) graphs. However, many streaming applications are modeled as cyclic CSDF graphs, thus they are not supported by such scheduling theory. Therefore, in this paper, we propose an approach which enables to apply the classical hard real-time scheduling theory on streaming applications modeled as cyclic CSDF graphs. The proposed approach converts each task in a cyclic CSDF graph to a constrained-deadline periodic task. This conversion enables the utilization of many hard real-time scheduling algorithms which offer properties such as temporal isolation and fast calculation of the required number of processors for scheduling the tasks. We evaluate the performance of our approach in comparison to existing scheduling approaches. The evaluation, on a set of real-life benchmarks, demonstrates that our approach can schedule the tasks in an application, modeled as a cyclic CSDF graph, with guaranteed throughput equal or comparable to the throughput obtained by existing scheduling approaches while providing hard real-time guarantees for every task in the application thereby enabling temporal isolation among concurrently running tasks/applications on a multi-processor platform.