Vehicles embed lots of sensors supporting driving and safety. Combined with connectivity, they bring new possibilities for Connected, Cooperative and Automated Mobility (CCAM) services that exploit local and global data for a wide understanding beyond the myopic view of local sensors. Internet of Things (IoT) messaging solutions are ideal for vehicular data as they ship core features like the separation of geographic areas, the fusion of different producers on data/sensor types, and concurrent subscription support. Multi-access Edge Computing (MEC) and Cloud infrastructures are key to hosting a virtualized and distributed IoT platform. Currently, the are no benchmarks for assessing the appropriate size of an IoT platform for multiple vehicular data types such as text, image, binary point clouds and video-formatted samples. This paper formulates and executes the tests to get a benchmarking of the performance of a MEC and Cloud platform according to actors' concurrency, data volumes and business levels parameters.

翻译：车辆集成了大量支持驾驶与安全的传感器。结合互联技术，这些传感器为连接、协作及自动化出行（CCAM）服务带来了全新可能——通过利用本地与全球数据，实现对局部传感器短视视角之外的广泛感知。物联网（IoT）消息传递解决方案因其具备地理区域分离、不同数据/传感器类型的生产者融合以及并行订阅支持等核心特性，成为处理车载数据的理想选择。多接入边缘计算（MEC）与云基础设施是承载虚拟化分布式物联网平台的关键。目前，针对文本、图像、二进制点云和视频格式样本等多类型车载数据，尚缺乏用于评估物联网平台适当规模的基准测试方法。本文通过设计并执行测试，根据参与者并发量、数据量及业务等级参数，对MEC与云平台的性能进行了基准评估。