ASDYS: Dynamic Scheduling Using Active Strategies for Multifunctional Mixed-Criticality Cyber–Physical Systems

Emerging cyber-physical systems (CPSs), such as in the domains of automotive, robotics, and industrial automation, often run complex functions with different criticality levels on a heterogeneous and distributed architecture. The ever stronger interactions between the cyber components and the physical environment lead to dynamic and irregular release of these functions. This article investigates dynamic scheduling of such mixed-criticality functions, where each function is modeled by a directed acyclic graph with no assumption on its period or minimum interarrival time. Unlike the existing methods that passively address the mixed criticality with a remedy when deadline misses are observed-this results in a high deadline miss ratio (DMR), and it is particularly undesirable for the high-criticality functions-we propose a novel dynamic scheduling approach using active strategies (ASDYS in short), where the mixed criticality is actively treated throughout the scheduling process. Automotive CPSs are used as an example for illustration. Experimental results show that our approach is significantly better than the existing methods in both the DMR of high-criticality functions and the overall system DMR.