DAG Hierarchical Schedulability Analysis for Avionics Hypervisor in Multicore Processors

Abstract

Parallel hierarchical scheduling of multicore processors in avionics hypervisor is being studied. Parallel hierarchical scheduling utilizes modular reasoning about the temporal behavior of the upper Virtual Machine (VM) by partitioning CPU time. Directed Acyclic Graphs (DAGs) are used for modeling functional dependencies. However, the existing DAG scheduling algorithm wastes resources and is inaccurate. Decreasing the completion time (CT) of DAG and offering a tight and secure boundary makes use of joint-level parallelism and inter-joint dependency, which are two key factors of DAG topology. Firstly, Concurrent Parent and Child Model (CPCM) is researched, which accurately captures the above two factors and can be applied recursively when parsing DAG. Based on CPCM, the paper puts forward a hierarchical scheduling algorithm, which focuses on decreasing the maximum CT of joints. Secondly, the new Response Time Analysis (RTA) algorithm is proposed, which offers a general limit for other execution sequences of Noncritical joints (NC-joints) and a specific limit for a fixed execution sequence. Finally, research results show that the parallel hierarchical scheduling algorithm has higher performance than other algorithms.