Software architectures play an important role in the success of cloud platforms in automotive domain. To review the architecture designs in this context, it is necessary to explore different design decisions such as design styles, quality attributes (QAs), and evaluation methodologies. To this end, we aimed to investigate (i) architectural design styles, (ii) major QAs, and (iii) architecture evaluation methods that are applied in the cloud platforms in automotive domain. We conducted an online survey to collect data from participants in industry and academia. Methodologies, such as descriptive statistics and grounded theory, were used to analyse the data. We collected 42 valid responses from participants with different roles, backgrounds, and years of experience. Considering the survey objectives, (i) event-driven and service-oriented architecture (SOA) were the most applied design styles to fulfil QAs. (ii) Availability, reliability, and security were the major QAs among other attributes. Finally, (iii) active reviews from intermediate design (ARID) and the scenario-based architecture analysis method (SAAM) were mostly applied when evaluating the architecture of cloud platforms in automotive domain. The results of our survey show a spectrum of different applicable design styles, QAs, and evaluation methods. For selecting the set of architectural design decisions, one should consider the business scenarios and relevant quality requirements that should be supported by the cloud platforms in automotive domain. Index Terms-Software architecture design, Cloud computing, Automotive, Internet of things (IoT) This research was supported by the ITEA3-APPSTACLE research project and funded by Business Finland.

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The emerging usage of connected vehicles promises new business models and a high level of innovation, but also poses new challenges for the automotive domain and in particular for the connectivity dimension, i. e. the connection between vehicles and cloud environments including the architecture of such systems. Among other challenges, IoT Cloud platforms and their services have to scale with the number of vehicles on the road to provide functionality in a reliable way, especially when dealing with safety-related functions. Testing the scalability, functionality, and availability of IoT Cloud platform architectures for connected vehicles requires data from real world scenarios instead of hypothetical data sets to ensure both the proper functionality of distinct connected vehicle services and that the architecture scales with a varying number of vehicles. However, the closed and proprietary nature of current connected vehicle solutions aggravate the availability of both vehicle data and test environments to evaluate different architectures and cloud solutions. Thus, this paper introduces an approach for connecting the Eclipse SUMO traffic simulation with the open source connected vehicle ecosystem Eclipse Kuksa. More precisely, Eclipse SUMO is used to simulate traffic scenarios including microscopic properties like the position or emission. The generated data of each vehicle is then be sent to the message gateway of the Kuksa IoT Cloud platform and delegated to an according example service that consumes the data. In this way, not only the scalability of connected vehicle IoT architectures can be tested based on real world scenarios, but also the functionality of cloud services can be ensured by providing context-specific automotive data that goes beyond rudimentary or fake data-sets.