Computing robustness of FlexRay schedules to uncertainties in design parameters

In the current environment of rapidly changing in-vehicle requirements and ever-increasing functional content for automotive EE systems, there are several sources of uncertainties in the definition of EE architecture design. This is also true for communication schedule synthesis where key decisions are taken early because of interactions with the suppliers. The possibility of change necessitates a design process that can analyze schedules for robustness to uncertainties, e.g., changes in estimated task durations or communication load. A robust design would be able to accommodate these changes incrementally without changes in the system scheduling, thus reducing validation times and increasing reusability. This paper introduces a novel approach based on the info-gap decision theory that provides a systematic scheme for analyzing robustness of schedules by computing the greatest horizon of uncertainty that still satisfies the performance requirements. The paper formulates info-gap models for potential uncertainties in schedule synthesis for a distributed automotive system communicating over a FlexRay network, and shows their application to a case study.