Software architectures of the convergence of automotive systems and cloud platforms

Abstract Context: Over the last few years, there has been an emerging interest towards connecting automotive systems to cloud platforms. This has created the urge to refactor system’s architectures that enable continuous and pervasive service provisioning and connectivity through federated networks and resources. The architectures should allow frequent software updates, complex data processes and algorithms and improved software quality in vehicles. Objective: The dissertation investigates and proposes software architecture solutions that aim at improving continuous software delivery in the automotive domain while alleviating quality concerns under the dynamic performing conditions in vehicles. Method: For this purpose, a combination of qualitative and quantitative methods was used for detailed analysis of previous literature, collecting architectural preferences from field experts, designing architectural solutions and evaluating the designed solutions in an experimental laboratory setting. Results: The results of this dissertation show that software architectures of the convergence of automotive systems and cloud platforms should address a wide range of quality concerns to fulfil different automotive scenarios. The findings indicate that the availability, reliability and scalability of services are among the major quality attributes to be addressed by software architectures. The findings of this dissertation show that microservices are a fully potential solution to address these quality concerns as well as other emerging requirements for continuous software delivery in the automotive domain. In addition, microservices are a design alternative to assure system designers about reliable, autonomous software functionalities under dynamic operating conditions in vehicles Contribution: A major contribution of this dissertation is to design, implement, and evaluate architectural artifacts that provide insight and empirical knowledge on quality research gaps and quality trade-offs in the software architectures of the convergence of automotive systems and cloud platforms. Furthermore, results of the systematic analysis of previous studies contribute to the literature by providing a synthesised and structured body of knowledge and a basis for future studies.Tiivistelmä Tausta: Viime vuosina on herännyt kiinnostusta yhdistää autojärjestelmät pilvialustoihin. Tästä on syntynyt tarve refaktoroida järjestelmän arkkitehtuurit, jotka mahdollistavat jatkuvan ja kokonaisvaltaisen palveluntarjonnan sekä liitettävyyden yhdistettyjen verkkojen ja resurssien avulla. Arkkitehtuurien tulisi mahdollistaa ajoneuvojen toistuvat ohjelmistopäivitykset, monimutkaiset tietojenkäsittelyprosessit ja algoritmit sekä parantaa ajoneuvojen ohjelmistojen laatua. Tavoite: Väitöskirjassa tutkitaan ja ehdotetaan ohjelmistoarkkitehtuuriratkaisuja, joilla pyritään parantamaan ohjelmistojen jatkuvaa toimittamista autoteollisuudessa ja samalla lieventämään ajoneuvojen dynaamisiin suorituskykyolosuhteisiin liittyviä laatuhuolia. Menetelmä: Tätä tarkoitusta varten käytettiin kvalitatiivisten ja kvantitatiivisten menetelmien yhdistelmää aiemman kirjallisuuden yksityiskohtaiseen analysointiin, arkkitehtonisten mieltymysten keräämiseen alan asiantuntijoilta, arkkitehtonisten ratkaisujen suunnitteluun ja suunniteltujen ratkaisujen arviointiin kokeellisissa laboratorio-olosuhteissa. Tulokset: Väitöskirjan tulokset osoittavat, että autojärjestelmien ja pilvialustojen yhdistettyjen ohjelmistoarkkitehtuurien tulisi vastata monenlaisiin laatuongelmiin erilaisten autoteollisuuden skenaarioiden toteuttamiseksi. Tulosten perusteella palvelujen saatavuus, luotettavuus ja skaalautuvuus ovat tärkeimpiä laatuominaisuuksia, joita ohjelmistoarkkitehtuureissa tulee käsitellä. Väitöskirjan tulokset esittävät, että mikropalvelut ovat täysin mahdollinen ratkaisu näihin laatuongelmiin sekä autoteollisuuden ohjelmistojen jatkuvaan toimitukseen liittyviin kasvaviin vaatimuksiin. Lisäksi mikropalvelut ovat suunnitteluvaihtoehto, jolla järjestelmäsuunnittelijat voidaan vakuuttaa luotettavista, itsenäisistä ohjelmistotoiminnoista ajoneuvojen dynaamisissa käyttöolosuhteissa. Kontribuutio: Tämän väitöskirjan keskeinen kontribuutio on arkkitehtonisten artefaktien suunnittelu, toteutus ja arviointi, jotka antavat käsityksen ja empiiristä tietoa laatuun liittyvistä tutkimusaukoista sekä kompromisseista autojärjestelmien ja pilvialustojen yhdistämisestä ohjelmistoarkkitehtuureissa. Lisäksi aikaisempien tutkimusten systemaattisen analyysin strukturoidut tulokset lisäävät ajantasaista tietämystä alan kirjallisuudessa ja luovat pohjan tulevalle tutkimukselle

Software architectures of the convergence of cloud computing and the Internet of Things:a systematic literature review

Abstract Context: Over the last few years, there has been an increasing interest in the convergence of cloud computing and the Internet of Things (IoT). Although software systems in this domain have attracted researchers to develop a large body of knowledge on software architecture designs, there is no systematic analysis of this knowledge. Objective: This study aims to identify and synthesise state-of-the-art architectural elements including the design patterns, styles, views, quality attributes, and evaluation methodologies in the convergence of cloud computing and IoT. Method: We used systematic literature review (SLR) methodology for a detailed analysis of 82 primary studies of a total of 1618 studies. Results: We extracted six architectural design patterns in this domain; among them, edge connectivity patterns stand out as the most popular choice. The service-oriented architecture is the most frequently applied style in this context. Among all applicable quality attributes, scalability, timeliness, and security were the most investigated quality attributes. In addition, we included nine cross analyses to address the relationship between architectural patterns, styles, views, and evaluation methodologies with respect to different quality attributes and application areas. Conclusions: Our findings indicate that research on software architectures in this domain is increasing. Although few studies were found in which industrial evaluations were presented, industry requires more scientific and empirically validated design frameworks to guide software engineering in this domain. This work provides an overview of the field while identifying areas for future research

Software architecture design of cloud platforms in automotive domain:an online survey

Abstract 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 the 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 the 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 the automotive domain

Bridging the gap between SUMO and Kuksa:using a traffic simulator for testing cloud-based connected vehicle services

Abstract 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

SUMO User Conference 2019

SUMO2019:Editor's Preface This volume contains the papers presented at the SUMO Conference 2019 Simulating Connected Urban Mobility. The conference was held in Berlin from 13-15 May 2019. The goal of the conference was to present new results in the field of mobility simulation and modelling using traffic tools and data which are open available.There were 32 submissions. Each submission was reviewed by at least 2 program committee members. The committee decided to accept 22 papers. Traffic simulations have a high value for traffic research studies. New traffic strategies can be tested and evaluated in advance with little costs. For realistic simulation results a complex traffic simulation framework is needed. One microscopic traffic simulation for this purpose is the open source tool Eclipse SUMO (Simulation of open mobility) which is available since 2001. SUMO provides a wide range of transport planning and modelling applications. The major topic of the 7th SUMO conference is the simulation of connected vehicles. This volume contains articles about simulator coupling, connected and automated Vehicles. Furthermore, the journal includes also papers about new algorithms for traffic light systems and new applications for the simulation of other traffic modes or reinforcement learning strategies. We would like to thank EasyChair for the conference support and its helpfull conference management tool. Laura Bieker-Walz Melanie Weber Robert Hilbrich Michael Behrisch July 24, 2019 Berli