Guaranteeing end-to-end deadlines for AUTOSAR-based automotive software

Abstract

Automotive electrical/electronic (E/E) architectures are evolving towards a complex software intensive distributed system. However, current technology and practice in the automotive industry do not adequately address the increasing complexity of software, which hinders accomplishing reliable, maintainable, high-quality software within time and budget constraints. Although automotive open system architecture (AUTOSAR) addresses many software issues such as system software services, application interfaces, and communication middleware, it largely focuses on the implementation aspect without sufficiently addressing the design aspect. In this paper, we present a novel approach to guaranteeing end-to-end deadlines for AUTOSAR-based automotive systems in the early design stage. Our approach, we call zero slack priority assignment (ZSPA), decomposes end-to-end deadlines into local per-task deadlines and finds a feasible scheduling solution leveraging the Audsley's optimal priority assignment algorithm. Our simulations show that ZSPA outperforms existing methods, heuristic optimized priority assignment (HOPA) (Garcia and Harbour, 1995) and the genetic algorithm (GA) (Azketa et al., 2011). Specifically, ZSPA shows up to 20% higher success rate in finding feasible solutions than HOPA and GA. The computational complexity of ZSPA is O(n(2)), whereas HOPA and GA have unbounded running time.