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The scheduling and schedulability analysis of real-time directed acyclicgraph (DAG) task systems have received much recent attention. The DAG model canaccurately represent intra-task parallelim and precedence constraints existingin many application domains. Existing techniques show that analyzing the DAGmodel is fundamentally more challenging compared to the ordinary sporadic taskmodel, due to the complex intra-DAG precedence constraints which may causerather pessimistic schedulability loss. However,such increased loss iscounter-intuitive because the DAG structure shall better exploit theparallelism provided by the multiprocessor platform. Our observation is thatthe intra-DAG precedence constraints, if not carefully considered by thescheduling algorithm, may cause very unpredictable execution behaviors ofsubtasks in a DAG and further cause pessimistic analysis. In this paper, wepresent a set of novel scheduling and analysis techniques for better supportinghard real-time sporadic DAG tasks on multiprocessors, through smartly definingand analyzing the execution order of subtasks in each DAG. Evaluationdemonstrates that our developed utilization-based schedulability test is highlyefficient, which dramatically improves schedulability of existingutilization-based tests by over 60% on average. Interestingly, when each DAG inthe system is an ordinary sporadic task, our test becomes identical to theclassical density test designed for the sporadic task model.

New Analysis Techniques for Supporting Hard Real-Time Sporadic DAG Task Systems on Multiprocessors