Vehicular clouds involve a dynamic environment where virtual machines are hosted on moving vehicles, leading to frequent changes in the data center network topology. These frequent topological changes require frequent virtual machine migrations in order to meet the service level agreements with cloud users. Such topology changes include fluctuations in connectivity, signal strength and quality. Few studies address vehicles as potential virtual machine hosts, while there is a significant opportunity in capitalizing on underutilized resources. Due to the rapidly changing environment of a vehicular cloud, hosts frequently change or leave coverage. As such, virtual machine management and migration schemes are necessary to ensure cloud subscribers have a satisfactory level of access to the resources. This thesis addresses the need for virtual machine management for the vehicular cloud. First, a mobility model is proposed and utilized to test a set of novel Vehicular Virtual Machine Migration (VVMM) schemes: VVMM-U (Uniform), VVMM-LW (Least Workload), VVMM-MA (Mobility Aware) and MDWLAM (Mobility and Destination Workload Aware Migration). Their performance is evaluated with respect to a set of metrics through simulations with varying levels of vehicular traffic congestion, virtual machine sizes and load restriction levels. The most advanced scheme (MDWLAM) takes into account the workload and mobility of the original host as well as those of the potential destinations. By doing so a valid destination will both have time to receive the workload and migrate the new load when necessary. The behavior of various algorithms is compared and the MDWLAM has been shown to demonstrate the best performance, exhibiting migration drop rates that are negligibly small. Finally, an integer linear program formulation based on a modified single source shortest path problem is presented, tested and successfully shown to be a benchmark that can be used in comparison to the proposed heuristics.

Intelligent transportation systems aim to provide innovative applications and services relating to traffic management and enable ease of access to information for various system users. The intent to utilize the excessive on-board resources in the transportation system, along with the latest computing resource management technology in conventional clouds, has cultivated the concept of the Vehicular Cloud. Evolved from Vehicular Networks, the vehicular cloud can be formed by vehicles autonomously, and provides a large number of applications and services that can benefit the entire transportation system, as well as drivers, passengers, and pedestrians. However, due to high traffic mobility, the vehicular cloud is built on dynamic physical resources; as a result, it experiences several inherent challenges, which increase the complexity of its implementations. Having a detailed picture of the number of vehicles, as well as their time of availability in a given region through a model, works as a critical stepping stone for enabling vehicular clouds, as well as any other system involving vehicles moving over the traffic network. The number of vehicles represents the amount of computation capabilities available in this region and the navigation time indicates the period of validity for a specific compute node. Therefore, in this thesis, we carry out a comprehensive stochastic analysis of several traffic characteristics related to the implementation of vehicular cloud inside a road segment by adopting proper traffic models. According to the analytical results, we demonstrate the feasibility of running a certain class of applications or services on the vehicular cloud, even for highly dynamic scenarios. Specifically, two kinds of traffic scenarios are modeled: free-flow traffic and queueing-up traffic. We use a macroscopic traffic model to investigate the free-flow traffic and analyze the features such as traffic density, the number of vehicles and their residence time. Also, we utilize the queueing theory to model the queueing-up traffic; the queue length and the waiting time in the queue are analyzed. The results show the boundaries on enabling vehicular cloud, allowing to determine a range of parameters for simulating vehicular clouds.

The emerging concept of vehicle cloudification is a promising solution to deal with ever-growing computational and communication demands of connected vehicles. A key idea is to have connected vehicles in the vicinity form a cluster which is called vehicular micro cloud. Vehicles in this micro cloud collaborate with other cluster members over vehicle-to-vehicle (V2V) networks for collective data processing, shared data storage, collaborative sensing and communication services. A typical use case of vehicular micro cloud is creation of a regional distributed data storage service, where member vehicles of the cloud collaboratively keep data contents in their on-board data storage devices. This allows vehicles in and around the vehicular micro cloud to request the contents from the micro cloud member(s) over vehicle-to-vehicle networks, or even update the data on the spot. In this thesis, we will discuss the need for vehicular micro clouds, followed by the architecture, formation of the micro clouds, and feasibility of micro clouds. Furthermore, we will cover aspects of efficient data transmission between vehicles, how to increase the scalability and to make it time efficient and cost efficient on practical road conditions for moving vehicles by encouraging coordination between neighboring micro cloud to help transfer data .

Vehicular ad hoc Networks (VANETs) allow vehicles to form a self-organized network. VANETs are likely to be widely deployed in the future, given the interest shown by industry in self-driving cars and satisfying their customers various interests. Problems related to Mobile ad hoc Networks (MANETs) such as routing, security, etc.have been extensively studied. Even though VANETs are special type of MANETs, solutions proposed for MANETs cannot be directly applied to VANETs because all problems related to MANETs have been studied for small networks. Moreover, in MANETs, nodes can move randomly. On the other hand, movement of nodes in VANETs are constrained to roads and the number of nodes in VANETs is large and covers typically large area. The following are the contributions of the thesis. Secure, authenticated, privacy preserving message dissemination in VANETs: When vehicles in VANET observe phenomena such as accidents, icy road condition, etc., they need to disseminate this information to vehicles in appropriate areas so the drivers of those vehicles can take appropriate action. When such messages are disseminated, the authenticity of the vehicles disseminating such messages should be verified while at the same time the anonymity of the vehicles should be preserved. Moreover, to punish the vehicles spreading malicious messages, authorities should be able to trace such messages to their senders when necessary. For this, we present an efficient protocol for the dissemination of authenticated messages. Incentive-based architecture for vehicular cloud: Due to the advantages such as exibility and availability, interest in cloud computing has gained lot of attention in recent years. Allowing vehicles in VANETs to store the collected information in the cloud would facilitate other vehicles to retrieve this information when they need. In this thesis, we present a secure incentive-based architecture for vehicular cloud. Our architecture allows vehicles to collect and store information in the cloud; it also provides a mechanism for rewarding vehicles that contributing to the cloud. Privacy preserving message dissemination in VANETs: Sometimes, it is sufficient to ensure the anonymity of the vehicles disseminating messages in VANETs. We present a privacy preserving message dissemination protocol for VANETs.

Au cours des dernières années, on a observé l'intérêt croissant envers l'accessibilité à l'information et, en particulier, envers des approches innovantes utilisant les services à distance accessibles depuis les appareils mobiles à travers le monde. Parallèlement, la communication des véhicules, utilisant des capteurs embarqués et des dispositifs de communication sans fil, a été introduite pour améliorer la sécurité routière et l'expérience de conduite à travers ce qui est communément appelé réseaux véhiculaires (VANET). L'accès sans fil à l’Internet à partir des véhicules a déclenché l'émergence de nouveaux services pouvant être disponibles à partir ceux-ci. Par ailleurs, une extension du paradigme des réseaux véhiculaires a été récemment promue à un autre niveau. Le nuage véhiculaire (Vehicular Cloud) (VC) est la convergence ultime entre le concept de l’infonuagique (cloud computing) et les réseaux véhiculaires dans le but de l’approvisionnement et la gestion des services. Avec cette approche, les véhicules peuvent être connectés au nuage, où une multitude de services sont disponibles, ou ils peuvent aussi être des fournisseurs de services. Cela est possible en raison de la variété des ressources disponibles dans les véhicules: informatique, bande passante, stockage et capteurs. Dans cette thèse, on propose des méthodes innovantes et efficaces pour permettre la délivrance de services par des véhicules dans le VC. Plusieurs schémas, notamment la formation de grappes ou nuages de véhicules, la planification de transmission, l'annulation des interférences et l'affectation des fréquences à l'aide de réseaux définis par logiciel (SDN), ont été développés et leurs performances ont été analysées. Les schémas de formation de grappes proposés sont DHCV (un algorithme de clustering D-hop distribué pour VANET) et DCEV (une formation de grappes distribuée pour VANET basée sur la mobilité relative de bout en bout). Ces schémas de regroupement sont utilisés pour former dynamiquement des nuages de véhicules. Les systèmes regroupent les véhicules dans des nuages qui ne se chevauchent pas et qui ont des tailles adaptées à leurs mobilités. Les VC sont créés de telle sorte que chaque véhicule soit au plus D sauts plus loin d'un coordonnateur de nuage. La planification de transmission proposée implémente un contrôle d'accès moyen basé sur la contention où les conditions physiques du canal sont entièrement analysées. Le système d'annulation d'interférence permet d'éliminer les interférences les plus importantes; cela améliore les performances de planification d’utilisation de la bande passante et le partage des ressources dans les nuages construits. Enfin, on a proposé une solution à l'aide de réseaux définis par logiciel, SDN, où différentes bandes de fréquences sont affectées aux différentes liens de transmission de chaque VC afin d’améliorer les performances du réseau. / Abstract : In recent years, we have observed a growing interest in information accessibility and especially innovative approaches for making distant services accessible from mobile devices across the world. In tandem with this growth of interest, there was the introduction of vehicular communication, also known as vehicular ad hoc networks (VANET), leveraging onboard sensors and wireless communication devices to enhance road safety and driving experience. Vehicles wireless accessibility to the internet has triggered the emergence of service packages that can be available to or from vehicles. Recently, an extension of the vehicular networks paradigm has been promoted to a new level. Vehicular cloud (VC) is the ultimate convergence between the cloud computing concept and vehicular networks for the purpose of service provisioning and management. Vehicles can get connected to the cloud, where a multitude of services are available to them. Also vehicles can offer services and act as service providers rather than service consumers. This is possible because of the variety of resources available in vehicles: computing, bandwidth, storage and sensors. In this thesis, we propose novel and efficient methods to enable vehicle service delivery in VC. Several schemes including cluster/cloud formation, transmission scheduling, interference cancellation, and frequency assignment using software defined networking (SDN) have been developed and their performances have been analysed. The proposed cluster formation schemes are DHCV (a distributed D-hop clustering algorithm for VANET) and DCEV (a distributed cluster formation for VANET based on end-to-end relative mobility). These clustering schemes are used to dynamically form vehicle clouds. The schemes group vehicles into non-overlapping clouds, which have adaptive sizes according to their mobility. VCs are created in such a way that each vehicle is at most D-hops away from a cloud coordinator. The proposed transmission scheduling implements a contention-free-based medium access control where physical conditions of the channel are fully analyzed. The interference cancellation scheme makes it possible to remove the strongest interferences; this improves the scheduling performance and resource sharing inside the constructed clouds. Finally, we proposed an SDN based vehicular cloud solution where different frequency bands are assigned to different transmission links to improve the network performance.

Today, the increasing number of applications based on the Internet of Things, as well as advances in wireless communication, information and communication technology, and mobile cloud computing have allowed users to access a wide range of resources while mobile. Vehicular clouds are considered key elements for today’s intelligent transportation systems. They are outfitted with equipment to enable applications and services for vehicle drivers, surrounding vehicles, pedestrians and third parties. As vehicular cloud computing has become more popular, due to its ability to improve driver and vehicle safety and provide provisioning services and applications, researchers and industry have growing interest in the design and development of vehicular networks for emerging applications. Though vehicle drivers can now access a variety of on-demand resources en route via vehicular network service providers, the development of vehicular cloud provisioning services has many challenges. In this dissertation, we examine the most critical provisioning service challenges drivers face, including, cost, privacy and latency. To this point, very little research has addressed these issues from the driver perspective. Privacy and service latency are certainly emerging challenges for drivers, as are service costs since this is a relatively new financial concept. Motivated by the Quality of Experience paradigm and the concept of the Trusted Third Party, we identify and investigate these challenges and examine the limitations and requirements of a vehicular environment. We found no research that addressed these challenges simultaneously, or investigated their effect on one another. We have developed a Quality of Experience framework that provides scalability and reduces congestion overhead for users. Furthermore, we propose two theory-based frameworks to manage on-demand service provision in vehicular clouds: Auction-driven Multi-objective Provisioning and a Multiagent/Multiobjective Interaction Game System. We present different approaches to these, and show through analytical and simulation results that our potential schemes help drivers minimize costs and latency, and maximize privacy.