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Worst-case response time analysis for partitioned fixed-priority DAG tasks on identical processors

The continuous integration of new functionality increases the complexity of embedded systems, while each functionality might impose precedence constraints between the programs fulfilling it. In addition, the prevalence of several processors may create the illusion of higher computation capacity easing the associated scheduling problem. However, this capacity is not exploitable in critical real time systems because of the increased variability of the execution times due to processor features designed to provide excellent average time behaviour and not necessarily ensuring small worst case bounds. This difficulty is added to the existence of scheduling anomalies when the systems are built on top of several processors. In this paper, we study the feasibility of independent tasks scheduled according to a given preemptive fixed-priority partitioned policy on identical processors. Each task is composed of several dependent subtasks related between them according to a directed acyclic graph (DAG). We provide a worst case response time analysis for DAG tasks when each sub-tasks have an individual priority level. This assumption allows to decrease the number of possible execution scenarios, making our analysis easier and less pessimistic.