The emergence of connected vehicles is driven by increasing customer and regulatory demands. To meet these, more complex software applications, some of which require service-based cloud and edge backends, are developed. When new software is deployed however, the high complexity and interdependencies between components can lead to unforeseen side effects in other system parts. As such, it becomes more challenging to recognize whether deviations to the intended system behavior are occurring, ultimately resulting in higher monitoring efforts and slower responses to errors. To overcome this problem, a simulation of the cloud environment running in parallel to the system is proposed. This approach enables the live comparison between simulated and real cloud behavior. Therefore, a concept is developed mirroring the existing cloud system into a simulation. To collect the necessary data, an observability platform is presented, capturing telemetry and architecture information. Subsequently, a simulation environment is designed that converts the architecture into a simulation model and simulates its dynamic workload by utilizing captured communication data. The proposed concept is evaluated in a real-world application scenario for electric vehicle charging: Vehicles can apply for an unoccupied charging station at a cloud service backend, the latter which manages all incoming requests and performs the assignment. Benchmarks are conducted by comparing the collected telemetry data with the simulated results under different loads and injected faults. The results show that regular cloud behavior is mirrored well by the simulation and that misbehavior due to fault injection is well visible, indicating that simulations are a promising data source for anomaly detection in connected vehicle cloud environments during operation.

翻译：联网车辆的出现是由日益增长的客户和监管需求驱动的。为满足这些需求，需要开发更复杂的软件应用程序，其中部分程序依赖于基于服务的云和边缘后端。然而，当新软件部署时，组件间的高度复杂性和相互依赖性可能导致其他系统部分出现不可预见的副作用。因此，识别系统行为是否偏离预期变得更具挑战性，最终导致监控工作量增加且对错误的响应变慢。为解决此问题，本文提出一种与系统并行运行的云环境模拟方法。该方法能够实时比较模拟云行为与实际云行为。为此，开发了一个将现有云系统镜像至模拟环境的概念。为了收集必要数据，提出了一种可观测性平台，用于捕获遥测数据和架构信息。随后设计了一个模拟环境，该环境将架构转换为模拟模型，并利用捕获的通信数据模拟其动态工作负载。所提出的概念在电动汽车充电的真实场景中进行了评估：车辆可向云服务后端申请空闲充电桩，该后端管理所有传入请求并执行分配。通过在不同负载和注入故障下比较收集的遥测数据与模拟结果进行基准测试。结果表明，模拟能较好地反映常规云行为，且故障注入导致的异常行为清晰可见，这表明模拟是联网车辆云环境运行期间异常检测的极具潜力的数据源。