Hard-Real-Time Scheduling of Data-Dependent Tasks in Embedded Streaming Applications
Most of the hard-real-time scheduling theory for multiprocessor systems assumes independent periodic or sporadic tasks. Such a simple task model is not directly applicable to modern embedded streaming applications. This is because a modern streaming application is typically modeled as a directed graph where nodes represent actors (i.e. tasks) and edges represent data-dependencies. The actors in such graphs have data-dependency constraints and do not necessarily conform to the periodic or sporadic task models. Therefore, in this paper the authors investigate the applicability of hard real-time scheduling theory for periodic tasks to streaming applications modeled as acyclic Cyclo-Static Data-Flow (CSDF) graphs.