Car-to-Cloud Communication Traffic Analysis Based on the Common Vehicle Information Model

Although connectivity services have been introduced already today in many of the most recent car models, the potential of vehicles serving as highly mobile sensor platform in the Internet of Things (IoT) has not been sufficiently exploited yet. The European AutoMat project has therefore defined an open Common Vehicle Information Model (CVIM) in combination with a cross-industry, cloud-based big data marketplace. Thereby, vehicle sensor data can be leveraged for the design of entirely new services even beyond traffic-related applications (such as localized weather forecasts). This paper focuses on the prediction of the achievable data rate making use of an analytical model based on empirical measurements. For an in-depth analysis, the CVIM has been integrated in a vehicle traffic simulator to produce CVIM-complaint data streams as a result of the individual behavior of each vehicle (speed, brake activity, steering activity, etc.). In a next step, a simulation of vehicle traffic in a realistically modeled, large-area street network has been used in combination with a cellular Long Term Evolution (LTE) network to determine the cumulated amount of data produced within each network cell. As a result, a new car-to-cloud communication traffic model has been derived, which quantifies the data rate of aggregated car-to-cloud data producible by vehicles depending on the current traffic situations (free flow and traffic jam). The results provide a reference for network planning and resource scheduling for car-to-cloud type services in the context of smart cities

6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities

Mobile communications have been undergoing a generational change every ten years or so. However, the time difference between the so-called "G's" is also decreasing. While fifth-generation (5G) systems are becoming a commercial reality, there is already significant interest in systems beyond 5G, which we refer to as the sixth-generation (6G) of wireless systems. In contrast to the already published papers on the topic, we take a top-down approach to 6G. We present a holistic discussion of 6G systems beginning with lifestyle and societal changes driving the need for next generation networks. This is followed by a discussion into the technical requirements needed to enable 6G applications, based on which we dissect key challenges, as well as possibilities for practically realizable system solutions across all layers of the Open Systems Interconnection stack. Since many of the 6G applications will need access to an order-of-magnitude more spectrum, utilization of frequencies between 100 GHz and 1 THz becomes of paramount importance. As such, the 6G eco-system will feature a diverse range of frequency bands, ranging from below 6 GHz up to 1 THz. We comprehensively characterize the limitations that must be overcome to realize working systems in these bands; and provide a unique perspective on the physical, as well as higher layer challenges relating to the design of next generation core networks, new modulation and coding methods, novel multiple access techniques, antenna arrays, wave propagation, radio-frequency transceiver design, as well as real-time signal processing. We rigorously discuss the fundamental changes required in the core networks of the future that serves as a major source of latency for time-sensitive applications. While evaluating the strengths and weaknesses of key 6G technologies, we differentiate what may be achievable over the next decade, relative to what is possible.Comment: Accepted for Publication into the Proceedings of the IEEE; 32 pages, 10 figures, 5 table

Named Data Networking in Vehicular Ad hoc Networks: State-of-the-Art and Challenges

International audienceInformation-Centric Networking (ICN) has been proposed as one of the future Internet architectures. It is poised to address the challenges faced by today's Internet that include, but not limited to, scalability, addressing, security, and privacy. Furthermore, it also aims at meeting the requirements for new emerging Internet applications. To realize ICN, Named Data Networking (NDN) is one of the recent implementations of ICN that provides a suitable communication approach due to its clean slate design and simple communication model. There are a plethora of applications realized through ICN in different domains where data is the focal point of communication. One such domain is Intelligent Transportation System (ITS) realized through Vehicular Ad hoc NETwork (VANET) where vehicles exchange information and content with each other and with the infrastructure. To date, excellent research results have been yielded in the VANET domain aiming at safe, reliable, and infotainment-rich driving experience. However, due to the dynamic topologies, host-centric model, and ephemeral nature of vehicular communication, various challenges are faced by VANET that hinder the realization of successful vehicular networks and adversely affect the data dissemination, content delivery, and user experiences. To fill these gaps, NDN has been extensively used as underlying communication paradigm for VANET. Inspired by the extensive research results in NDN-based VANET, in this paper, we provide a detailed and systematic review of NDN-driven VANET. More precisely, we investigate the role of NDN in VANET and discuss the feasibility of NDN architecture in VANET environment. Subsequently, we cover in detail, NDN-based naming, routing and forwarding, caching, mobility, and security mechanism for VANET. Furthermore, we discuss the existing standards, solutions, and simulation tools used in NDN-based VANET. Finally, we also identify open challenges and issues faced by NDN-driven VANET and highlight future research directions that should be addressed by the research community

Street Smart in 5G : Vehicular Applications, Communication, and Computing

Recent advances in information technology have revolutionized the automotive industry, paving the way for next-generation smart vehicular mobility. Specifically, vehicles, roadside units, and other road users can collaborate to deliver novel services and applications that leverage, for example, big vehicular data and machine learning. Relatedly, fifth-generation cellular networks (5G) are being developed and deployed for low-latency, high-reliability, and high bandwidth communications. While 5G adjacent technologies such as edge computing allow for data offloading and computation at the edge of the network thus ensuring even lower latency and context-awareness. Overall, these developments provide a rich ecosystem for the evolution of vehicular applications, communications, and computing. Therefore in this work, we aim at providing a comprehensive overview of the state of research on vehicular computing in the emerging age of 5G and big data. In particular, this paper highlights several vehicular applications, investigates their requirements, details the enabling communication technologies and computing paradigms, and studies data analytics pipelines and the integration of these enabling technologies in response to application requirements.Peer reviewe

Ein mehrschichtiges sicheres Framework für Fahrzeugsysteme

In recent years, significant developments were introduced within the vehicular domain, evolving the vehicles to become a network of many embedded systems distributed throughout the car, known as Electronic Control Units (ECUs). Each one of these ECUs runs a number of software components that collaborate with each other to perform various vehicle functions. Modern vehicles are also equipped with wireless communication technologies, such as WiFi, Bluetooth, and so on, giving them the capability to interact with other vehicles and roadside infrastructure. While these improvements have increased the safety of the automotive system, they have vastly expanded the attack surface of the vehicle and opened the door for new potential security risks. The situation is made worse by a lack of security mechanisms in the vehicular system which allows the escalation of a compromise in one of the non-critical sub-systems to threaten the safety of the entire vehicle and its passengers. This dissertation focuses on providing a comprehensive framework that ensures the security of the vehicular system during its whole life-cycle. This framework aims to prevent the cyber-attacks against different components by ensuring secure communications among them. Furthermore, it aims to detect attacks which were not prevented successfully, and finally, to respond to these attacks properly to ensure a high degree of safety and stability of the system.In den letzten Jahren wurden bedeutende Entwicklungen im Bereich der Fahrzeuge vorgestellt, die die Fahrzeuge zu einem Netzwerk mit vielen im gesamten Fahrzeug verteile integrierte Systeme weiterentwickelten, den sogenannten Steuergeräten (ECU, englisch = Electronic Control Units). Jedes dieser Steuergeräte betreibt eine Reihe von Softwarekomponenten, die bei der Ausführung verschiedener Fahrzeugfunktionen zusammenarbeiten. Moderne Fahrzeuge sind auch mit drahtlosen Kommunikationstechnologien wie WiFi, Bluetooth usw. ausgestattet, die ihnen die Möglichkeit geben, mit anderen Fahrzeugen und der straßenseitigen Infrastruktur zu interagieren. Während diese Verbesserungen die Sicherheit des Fahrzeugsystems erhöht haben, haben sie die Angriffsfläche des Fahrzeugs erheblich vergrößert und die Tür für neue potenzielle Sicherheitsrisiken geöffnet. Die Situation wird durch einen Mangel an Sicherheitsmechanismen im Fahrzeugsystem verschärft, die es ermöglichen, dass ein Kompromiss in einem der unkritischen Subsysteme die Sicherheit des gesamten Fahrzeugs und seiner Insassen gefährdet kann. Diese Dissertation konzentriert sich auf die Entwicklung eines umfassenden Rahmens, der die Sicherheit des Fahrzeugsystems während seines gesamten Lebenszyklus gewährleistet. Dieser Rahmen zielt darauf ab, die Cyber-Angriffe gegen verschiedene Komponenten zu verhindern, indem eine sichere Kommunikation zwischen ihnen gewährleistet wird. Darüber hinaus zielt es darauf ab, Angriffe zu erkennen, die nicht erfolgreich verhindert wurden, und schließlich auf diese Angriffe angemessen zu reagieren, um ein hohes Maß an Sicherheit und Stabilität des Systems zu gewährleisten