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

Integrated wireless access and networking to support floating car data collection in vehicular networks

Collecting data from a large number of agents scattered over a region of interest is becoming an increasingly appealing paradigm to feed big data archives that lay the ground for a vast array of applications. Vehicular Floating Car Data (FCD) collection, a major representative of this paradigm, is a key enabler for a wide range of Intelligent Transportation Systems (ITS) services and applications aiming at enhancing safety, efficiency and sustainability. Obtaining real time, high spacial and temporal resolution vehicular FCD information is becoming a reality thanks to the variety of communication platforms that are being deployed. Dedicated Short-Range Communication (DSRC) and Long Term Evolution (LTE) are the most prominent communication technologies able to support periodic and persistent FCD collection. DSRC technology was mainly proposed for safety applications and is specifically tailored for Vehicular Ad Hoc Networks (VANETs). The first parts of this work are dedicated to assessing the suitability of DSRC to support FCD collection in real urban scenarios. We first study the basic communication paradigm that takes place in VANETs to populate vehicles’ local data bases with FCD information, named beaconing, and the trade-off between the beaconing frequency and the congestion induced in the wireless shared channel used to exchange these beacons. The primary metric to measure the information freshness inside every vehicle’s local data base is the Age-of-Information (AoI). We define an analytical model to evaluate the AoI of a VANET, given the connectivity graph of the vehicles, and validate the model by comparing it with realistic simulations of an urban area. Then, we propose an integrated DSRC-based protocol that disseminates queries and collects FCD messages from vehicles roaming in a quite large city area efficiently and timely by using a single network structure, i.e., a multi-hop backbone network made up of only vehicle nodes. The proposed solution is distributed and adaptive to different traffic conditions, i.e., to different levels of vehicular traffic density. One of the main protocol advantages is that for the dissemination of queries it exploits an existing standardized data dissemination algorithm, namely the GeoNetworking Contention-Based Forwarding (CBF). The proposed protocol is evaluated with reference to a real urban environment. The main parameters are dimensioned and an insight into the protocol operation is given. One of the main outcomes of this part of the thesis is the confirmation of the fact that DSRC is suitable to support not only safety applications, but also periodic FCD collection. The main issue with DSRC is the low penetration rate. LTE on the other hand is pervasive and has been identified as a good candidate technology for non-safety applications. However, a high number of vehicles intermittently reporting their information via LTE can introduce a very high load on the LTE access network. The second part of this work addresses the design and performance evaluation of heterogeneous LTE-DSRC networking solutions to yield significant offloading of LTE – here, DSRC technology can support local data aggregation. We propose distributed clustering algorithms that use both LTE and DSRC networks in the cluster head selection process. We target robustness, optimizing the amount of data and the value of the collection period, keeping in mind the goals of autonomous node operation and minimal coordination effort. Our results clearly indicate that it is crucial to consider parameters drawn from both networking platforms for selecting the right forwarders. We demonstrate that our solutions are able to significantly reduce the LTE channel utilization with respect to other state-of-the-art approaches. The impact of the proposed protocols on the DSRC channels’ load is evaluated and proved to be quite small, so that it does not interfere with other VANET-specific messages

Software-defined Networking enabled Resource Management and Security Provisioning in 5G Heterogeneous Networks

Due to the explosive growth of mobile data traffic and the shortage of spectral resources, 5G networks are envisioned to have a densified heterogeneous network (HetNet) architecture, combining multiple radio access technologies (multi-RATs) into a single holistic network. The co-existing of multi-tier architectures bring new challenges, especially on resource management and security provisioning, due to the lack of common interface and consistent policy across HetNets. In this thesis, we aim to address the technical challenges of data traffic management, coordinated spectrum sharing and security provisioning in 5G HetNets through the introduction of a programmable management platform based on Software-defined networking (SDN). To address the spectrum shortage problem in cellular networks, cellular data traffic is efficiently offloaded to the Wi-Fi network, and the quality of service of user applications is guaranteed with the proposed delay tolerance based partial data offloading algorithm. A two-layered information collection is also applied to best load balancing decision-making. Numerical results show that the proposed schemes exploit an SDN controller\u27s global view of the HetNets and take optimized resource allocation decisions. To support growing vehicle-generated data traffic in 5G-vehicle ad hoc networks (VANET), SDN-enabled adaptive vehicle clustering algorithm is proposed based on the real-time road traffic condition collected from HetNet infrastructure. Traffic offloading is achieved within each cluster and dynamic beamformed transmission is also applied to improve trunk link communication quality. To further achieve a coordinated spectrum sharing across HetNets, an SDN enabled orchestrated spectrum sharing scheme that integrates participating HetNets into an amalgamated network through a common configuration interface and real-time information exchange is proposed. In order to effectively protect incumbent users, a real-time 3D interference map is developed to guide the spectrum access based on the SDN global view. MATLAB simulations confirm that average interference at incumbents is reduced as well as the average number of denied access. Moreover, to tackle the contradiction between more stringent latency requirement of 5G and the potential delay induced by frequent authentications in 5G small cells and HetNets, an SDN-enabled fast authentication scheme is proposed in this thesis to simplify authentication handover, through sharing of user-dependent secure context information (SCI) among related access points. The proposed SCI is a weighted combination of user-specific attributes, which provides unique fingerprint of the specific device without additional hardware and computation cost. Numerical results show that the proposed non-cryptographic authentication scheme achieves comparable security with traditional cryptographic algorithms, while reduces authentication complexity and latency especially when network load is high

Dynamic Vehicular Routing in Urban Environments

Traffic congestion is a persistent issue that most of the people living in a city have to face every day. Traffic density is constantly increasing and, in many metropolitan areas, the road network has reached its limits and cannot easily be extended to meet the growing traffic demand. Intelligent Transportation System (ITS) is a world wide trend in traffic monitoring that uses technology and infrastructure improvements in advanced communication and sensors to tackle transportation issues such as mobility efficiency, safety, and traffic congestion. The purpose of ITS is to take advantage of all available technologies to improve every aspect of mobility and traffic. Our focus in this thesis is to use these advancements in technology and infrastructure to mitigate traffic congestion. We discuss the state of the art in traffic flow optimization methods, their limitations, and the benefits of a new point of view. The traffic monitoring mechanism that we propose uses vehicular telecommunication to gather the traffic information that is fundamental to the creation of a consistent overview of the traffic situation, to provision real-time information to drivers, and to optimizing their routes. In order to study the impact of dynamic rerouting on the traffic congestion experienced in the urban environment, we need a reliable representation of the traffic situation. In this thesis, traffic flow theory, together with mobility models and propagation models, are the basis to providing a simulation environment capable of providing a realistic and interactive urban mobility, which is used to test and validate our solution for mitigating traffic congestion. The topology of the urban environment plays a fundamental role in traffic optimization, not only in terms of mobility patterns, but also in the connectivity and infrastructure available. Given the complexity of the problem, we start by defining the main parameters we want to optimize, and the user interaction required, in order to achieve the goal. We aim to optimize the travel time from origin to destination with a selfish approach, focusing on each driver. We then evaluated constraints and added values of the proposed optimization, providing a preliminary study on its impact on a simple scenario. Our evaluation is made in a best-case scenario using complete information, then in a more realistic scenario with partial information on the global traffic situation, where connectivity and coverage play a major role. The lack of a general-purpose, freely-available, realistic and dependable scenario for Vehicular Ad Hoc Networks (VANETs) creates many problems in the research community in providing and comparing realistic results. To address these issues, we implemented a synthetic traffic scenario, based on a real city, to evaluate dynamic routing in a realistic urban environment. The Luxembourg SUMO Traffic (LuST) Scenario is based on the mobility derived from the City of Luxembourg. The scenario is built for the Simulator of Urban MObiltiy (SUMO) and it is compatible with Vehicles in Network Simulation (VEINS) and Objective Modular Network Testbed in C++ (OMNet++), allowing it to be used in VANET simulations. In this thesis we present a selfish traffic optimization approach based on dynamic rerouting, able to mitigate the impact of traffic congestion in urban environments on a global scale. The general-purpose traffic scenario built to validate our results is already being used by the research community, and is freely-available under the MIT licence, and is hosted on GitHub