Optimizing Extensibility of CAN FD for Automotive Cyber-Physical Systems

Abstract

Extensibility is an important optimization objective for the E/E architecture of automotive cyber-physical systems (ACPS), while little attention has paid to the extensibility-aware design of in-vehicle network. To address this problem, this paper formulates a trade-off problem that balances the bandwidth utilization and the extensibility from the initial design of CAN FD. We firstly propose a new extensibility model and the related evaluation metric, and then two optimization algorithms, namely, the mixed integer linear programming (MILP) approach and the simulated annealing (SA) based heuristic approach, are proposed to resolve the trade-off problem for mid-sized and industry sized signal sets, respectively. The experiment results show the efficiency of the proposed extensibility metric and the optimization algorithms. By comparing with state-of-the-art algorithm, the MILP reduces the increase range of the bandwidth utilization of the extended signal set by 18.17% to 57.64% averagely, and 49.22% to 89.40% maximally, with only 0.06% to 0.79% bandwidth utilization overhead; the SA approach can reduces the increase range of the bandwidth utilization of the extended signal set by 12.71% to 58.33% averagely, and 40.08% to 89.40% maximally, with only 0.06% to 0.8% bandwidth utilization overhead.