Modern vehicles are embedding increasing levels of automation, connectivity, and intelligence, which require advanced in-vehicle networks and computational platforms to support the dependability and deterministic requirements of critical in-vehicle functions. To this end, the automotive industry is shifting towards software-defined vehicles (SDVs) and zonal E/E architectures with centralized computing nodes. Realizing the full potential of these new architectures requires an efficient management of the in-vehicles computational workload. In this context, this paper introduces a deterministic task scheduling approach for in-vehicle networks (IVN), and demonstrates that it can better guarantee deterministic service levels than alternative approaches based on the shortest path or the objective to minimize task execution time. Our evaluation also demonstrates that a deterministic task scheduling can satisfactorily support increasing in-vehicle computational workloads and tasks, and achieve a more balanced workload and resource utilization across the IVN. These gains are validated across a variety of IVN topologies, and in hybrid wireless-wired IVN implementations, where a gradual introduction of wireless offers increased in-vehicle connectivity diversity.

翻译：现代汽车正嵌入越来越多的自动化、连接性和智能化功能，这需要先进的车载网络和计算平台来支持关键车载功能的可靠性与确定性需求。为此，汽车行业正转向软件定义汽车（SDV）和具有集中式计算节点的分区电子电气架构。要充分实现这些新架构的潜力，必须有效管理车载计算工作负载。在此背景下，本文提出了一种面向车载网络（IVN）的确定性任务调度方法，并证明该方法能比基于最短路径或最小化任务执行时间的目标的替代方案更好地保证确定性服务水平。我们的评估还表明，确定性任务调度能够充分支持日益增长的车载计算工作负载与任务，并在整个IVN中实现更均衡的工作负载与资源利用率。这些优势在多种IVN拓扑结构以及混合无线-有线IVN实现中均得到验证，其中逐步引入无线连接可提高车载连接的多样性。