Abstract

nnually, millions of people die and many more sustain non-fatal injuries because of road traffic crashes. Despite multitude of countermeasures, the number of causalities and disabilities owing to traffic accidents are increasing each year causing grinding social, economic, and health problems. Due to their high volume and lack of protective-shells, more than half of road traffic deaths are imputed to vulnerable road users (VRUs): pedestrians, cyclists and motorcyclists. Mobile devices combined with fog computing can provide feasible solutions to protect VRUs by predicting collusions and warning users of an imminent traffic accident. Mobile devices’ ubiquity and high computational capabilities make the devices an important components of traffic safety solutions. Fog computing has features that suits to traffic safety applications as it is an extension of cloud computing that brings down computing, storage, and network services to the proximity of end user. Therefore, in this thesis, we have proposed an infrastructure-less traffic safety architecture that depends on fog computing and mobile devices possessed by VRUs and drivers. The main duties of mobile devices are extracting their positions and other related data and sending cooperative awareness message to a nearby fog server using wireless connection. The fog server estimates collision using a collision prediction algorithm and sends an alert message, if an about-to-occur collision is predicted. Evaluation results shows that the proposed architecture is able to render alerts in real time. Moreover, analytical and performance evaluations depict that the architecture outperforms other related road safety architectures in terms of reliability, scalability and latency. However, before deploying the architecture, challenges pertaining to weaknesses of important ingredients of the architecture should be treated prudently. Position read by mobile devices are not accurate and do not meet maximum position sampling rates traffic safety applications demand. Moreover, continuous and high rate position sampling drains mobile devices battery quickly. From fog computing’s point of view, it confronts new privacy and security challenges in addition to those assumed from cloud computing. For aforementioned challenges, we have proposed new solutions: (i) In order to improve GPS accuracy, we have proposed an efficient and effective two-stage map matching algorithm. In the first stage, GPS readings obtained from smartphones are passed through Kalman filter to smooth outlier readings. In the second stage, the smoothed positions are mapped to road segments using online time warping algorithm. (ii) position sampling frequency requirement is fulfilled by an energy efficient location prediction system that fuses GPS and inertial sensors’ data. (iii) For energy efficiency, we proposed an energy efficient fuzzy logic-based adaptive beaconing rate management that ensures safety of VRUs. (iv) finally, privacy and security issues are addressed indirectly using trust management system. The two-way subjective logic-based trust management system enables fog clients to evaluate the trust level of fog servers before awarding the service and allows the servers to check out the trustworthiness of the service demanders. Engaging omnipresent mobile device and QoS-aware fog computing paradigm in active traffic safety applications has the potential to reduce overwhelming number of traffic accidents on VRUs.; Chaque année, des millions de personnes meurent et beaucoup d'autres subissent des séquelles graves à la suite d'accidents de la route. Malgré une multitude d’initiatives, le nombre de cas mortels et d'accidents graves augmente chaque année en engendrant des problèmes préoccupants à la fois sociaux, économiques et sanitaires. En raison de leur nombre élevé et de l'absence de protection personnelle, plus de la moitié de ces décès concerne les usagers vulnérables (en anglais, vulnerable road users - VRU) regroupant les piétons, cyclistes et motocyclistes. Les appareils mobiles, combinés à la technologie de Fog Computing (ou informatique géodistribuée, ou même informatique en brouillard), représentent une solution réaliste à court terme pour les protéger en les avertissant de l’imminence d'un accident de circulation. L’omniprésence des appareils mobiles et leurs capacités de calcul élevées font de ces appareils un élément important à considérer dans les solutions de sécurité routière. Le Fog Computing offre des fonctionnalités adaptées aux applications de sécurité routière, puisqu’il s’agit d’une extension du Cloud Computing permettant de rapprocher les services informatiques, le stockage et le réseau au plus près des utilisateurs finaux. Par conséquent, dans cette thèse, nous proposons une architecture réseau sans infrastructure supplémentaire (PV-Alert) pour des fins de sécurité routière et reposant uniquement sur les appareils mobiles des VRU et des conducteurs sur la route avec l’aide du concept de Fog Computing. Les données géographiques et cinématiques de ces appareils sont collectées et envoyées périodiquement au serveur fog situé à proximité. Le serveur fog traite ces données en exécutant un algorithme de calcul de risque d’accident de circulation et renvoie des notifications en cas d'accident imminent. L’évaluation de cette architecture montre qu’elle est capable de générer des alertes en temps réel et qu’elle est plus performante que d’autres architectures en termes de fiabilité, d’évolutivité et de latence.

Abstract

This paper discusses some challenges that user mobility imposes over the user-centric protection model against security threats. This model is based on the idea of offloading the security applications from the end user device, and placing them in a trusted network node at the network's edge. Our research perspective is particularly centered around three interrelated mobility challenges, i) the allocation of the security applications “close” to the user, i.e., on network nodes with enhanced processing capabilities, ii) seamless mobility with negligible disruption of ongoing network connections, and iii) dynamic orchestration and management with support of security applications migration. Based on our arguments, we expose the main requirements and trade-offs to be considered in the attempt to support mobility in such environment. We propose a flexible solution that leverages Software Defined Networking, Network Function Virtualization and Computing at the Network Edge to offer a seamless on-path security protection to mobile users. Our preliminary experiments' results considering a WiFi mobile user show that seamless security migration and mobility are feasible in a simple real scenario. Vertical mobility and more complex use cases scenarios are envisioned for future research. Peer Reviewed Document type: Conference object

Abstract

International audience; Fog Computing is a recent computing paradigm that is extending cloud computing towards the edge of network. Due to its proximity to end-users, dense geographical distribution, open platform and support for high mobility, Fog Computing platforms can provide services with reduced latency and improved QoS. Thus it is becoming an important enabler for consumer centric Internet of Things based applications and services that require real time operations e.g. connected vehicles, smart road intersection management and smart grid. The paper discusses one such architecture for connected vehicles with Road Side Units (RSUs) and M2M gateways including the Fog Computing Platform. M2M data processing with semantics, discovery and management of connected vehicles are briefly discussed as consumer centric IoT services enabled by the distinct characteristics of Fog Computing.

Abstract

International audience; High volumes of pedestrians, cyclists and other vulnerable road users (VRUs) have much higher casualty rates per mile; not surprising given their lack of protection from an accident. In order to alleviate the problem, sensing capabilities of smartphones can be used to detect, warn and safeguard these road users. In this research we propose an infrastructure-less fog-based architecture named PV-Alert (Pedestrian-Vehicle Alert) where fog nodes process delay sensitive data obtained from smartphones for alerting pedestrians and drivers before sending the data to the cloud for further analysis. Fog computing is considered in developing the architecture since it is an emerging paradigm that has paramount of advantages for low-latency applications which demand mobility support, geo-distribution and location awareness. We have also defined an algorithm for accident prediction and alerting traffic accidents involving vehicles and pedestrians. PV-Alert can be deployed quickly since it is based only on users' smartphones and doesn't require special infrastructure. Simulation results show that the proposed architecture is able to render alerts in real time whichever the wireless communication technology used to connect smartphones with fog nodes (Wi-Fi or LTE). Moreover, analytical and performance evaluations depict that the new architecture outperforms other related architectures in terms of reliability, scalability and latency.

Abstract

Traffic congestion and accidents cause cities to be the principal source of pollutant emissions. The TIMON project initiative aims at providing Real-Time (RT) information and cloud-based services through an open web-based platform and a mobile application to the main actors: drivers, vulnerable road users and businesses. TIMON establishes a cooperative ecosystem to connect people, vehicles, infrastructure and business and contributes to intelligent transport, IoT and Cloud computing. In the first part, this paper provides an overview of TIMON and how it contributes to increasing safety and reducing congestion and emissions. The TIMON ecosystem represents the perfect use case of distributed technologies, as it collects data from IoT sensors, open and closed data sources and user engagement data, processes it and provides useful information not only for road users, but also for scientists and technicians who need real systems to study the data, infrastructure and IT safety management. In the second part, the Cloud deployment of the TIMON system is described in detail and a new, more distributed design is proposed to exploit the potential of current emerging technologies of Fog and Edge computing. Document type: Conference object

Abstract

The adoption of advanced Internet of Things (IoT) technologies has impressively improved in recent years by placing such services at the extreme Edge of the network. There are, however, specific Quality of Service (QoS) trade-offs that must be considered, particularly in situations when workloads vary over time or when IoT devices are dynamically changing their geographic position. This article proposes an innovative capillary computing architecture, which benefits from mainstream Fog and Cloud computing approaches and relies on a set of new services, including an Edge/Fog/Cloud Monitoring System and a Capillary Container Orchestrator. All necessary Microservices are implemented as Docker containers, and their orchestration is performed from the Edge computing nodes up to Fog and Cloud servers in the geographic vicinity of moving IoT devices. A car equipped with a Motorhome Artificial Intelligence Communication Hardware (MACH) system as an Edge node connected to several Fog and Cloud computing servers was used for testing. Compared to using a fixed centralized Cloud provider, the service response time provided by our proposed capillary computing architecture was almost four times faster according to the 99th percentile value along with a significantly smaller standard deviation, which represents a high QoS. Document type: Article