Efficient maximum data age analysis for cause-effect chains in automotive systems
Ran Bi, Xinbin Liu, Jiankang Ren, Pengfei Wang, Huawei Lv, Guozhen Tan
Abstract
Automotive systems are often subjected to stringent requirements on the maximum data age of certain cause-effect chains. In this paper, we present an efficient method for formally analyzing maximum data age of cause-effect chains. In particular, we decouple the problem of bounding the maximum data age of a chain into a problem of bounding the releasing interval of successive Last-to-Last data propagation instances in the chain. Owing to the problem decoupling, a relatively tighter data age upper bound can be effectively obtained in polynomial time. Experiments demonstrate that our approach can achieve high precision analysis with lower computational cost.
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