Philosophiae Doctor - PhD / Unmanned Aerial Vehicles (UAVs) have recently o ered signi cant technological achievements. The advancement in related applications predicts an extended need for automated data muling by UAVs, to explore high risk places, ensure e ciency and reduce the cost of various products and services. Due to advances in technology, the actual UAVs are not as expensive as they once were. On the other hand, they are limited in their ight time especially if they have to use fuel. As a result, it has recently been proposed that they could be assisted by the ground static sensors which provide information of their surroundings. Then, the UAVs need only to provide actions depending on information received from the ground sensors. In addition, UAVs need to cooperate among themselves and work together with organised ground sensors to achieve an optimal coverage. The system to handle the cooperation of UAVs, together with the ground sensors, is still an interesting research topic which would bene t both rural and urban areas. In this thesis, an e cient ground sensor network for optimal UAVs coverage is rst proposed. This is done using a clustering scheme wherein, each cluster member transmits its sensor readings to its cluster head. A more e cient routing scheme for delivering readings to cluster head(s) for collection by UAVs is also proposed. Furthermore, airborne sensor deployment models are provided for e cient data collection from a unique sensor/target. The model proposed for this consists of a scheduling technique which manages the visitation of UAVs to target. Lastly, issues relating to the interplay between both types of sensor (airborne and ground/underground) networks are addressed by proposing the optimal UAVs task allocation models; which take caters for both the ground networking and aerial deployment. Existing network and tra c engineering techniques were adopted in order to handle the internetworking of the ground sensors. UAVs deployment is addressed by adopting Operational Research techniques including dynamic assignment and scheduling models. The proposed models were validated by simulations, experiments and in some cases, formal methods used to formalise and prove the correctness of key properties.

Cloud computing has brought availability of services at unprecedented scales but data accessibility considerations become more complex due to involvement of multiple parties in providing the infrastructure. In this thesis, we discuss the problem of enabling cooperative data access in a multi-cloud environment where the data is owned and managed by multiple enterprises. We consider a multi-party collaboration scheme whereby a set of parties collectively decide accessibility to data from individual parties using different data models such as relational databases, and graph databases. In order to implement desired business services, parties need to share a selected portion of information with one another. We consider a model with a set of authorization rules over the joins of basic relations, and such rules are defined by these cooperating parties. The accessible information is constrained by these rules. Specifically, the following critical issues were examined: Combine rule enforcement and query planning and devise an algorithm which simultaneously checks for the enforceability of each rule and generation of minimum cost plan of its execution using a cost metric whenever the enforcement is possible; We also consider other forms of limiting the access to the shared data using safety properties and selection conditions. We proposed algorithms for both forms to remove any conflicts or violations between the limited accesses and model queries; Used graph databases with our authorization rules and query planning model to conduct similarity search between tuples, where we represent the relational database tuples as a graph with weighted edges, which enables queries involving "similarity" across the tuples. We proposed an algorithm to exploit the correlations between attributes to create virtual attributes that can be used to catch much of the data variance, and enhance the speed at which similarity search occurs; Proposed a framework for defining test functionalities their composition, and their access control. We discussed an algorithm to determine the realization of the given test via valid compositions of individual functionalities in a way to minimize the number of parties involved. The research significance resides in solving real-world issues that arise in using cloud services for enterprises After extensive evaluations, results revealed: collaborative data access model improves the security during cooperative data processes; systematic and efficient solving access rules conflict issues minimizes the possible data leakage; and, a systematic approach tackling control failure diagnosis helps reducing troubleshooting times and all that improve availability and resiliency. The study contributes to the knowledge, literature, and practice. This research opens up the space for further studies in various aspects of secure data cooperation in large-scale cyber and cyber-physical infrastructures. / Computer and Information Science

Dans le cadre des systèmes de transport intelligents (STI), les véhicules peuvent avoir beaucoup de capteurs (caméras, lidars, radars, etc.) et d’applications (évitement des collisions, surveillance du trafic, etc.) générant des données. Ils représentent alors une source d’information importante. Les applications locales peuvent augmenter considérablement leur efficacité en partageant une telle information au sein du réseau. La précision des données, la confiance et la pertinence peuvent être vérifiées lors de la réception de données provenant d’autres nœuds. Par conséquent, nous croyons qu’une question importante à répondre dans ce contexte est: “Comment partager efficacement les données dans un tel environnement?” Le partage de données est une tâche complexe dans les réseaux dynamiques. De nombreuses problèmes telles que les connexions intermittentes, la variation de la densité du réseau et la congestion du médium de communication se posent. Une approche habituelle pour gérer ces problèmes est basée sur des processus périodiques. En effet, un message envoyé plusieurs fois peut atteindre sa destination même avec des connexions intermittentes et des réseaux à faible densité. Néanmoins, dans les réseaux à haute densité, ils peuvent entraîner une congestion du médium de communication. Dans cette thèse, nous abordons le problème du partage de données dans des réseaux dynamiques en nous appuyant sur des horizons de pertinence. Un horizon est défini comme une zone dans laquelle une information devrait être reçue. Nous commençons par nous concentrer sur le partage de données au sein des voisins directs (à 1 saut de distance). Ensuite, nous proposons une solution pour construire une carte des voisins, centrée sur le nœud ego, dans un horizon à n sauts. Enfin, nous relâchons la définition de l’horizon pour la définir de façon dynamique, où différents éléments de données peuvent atteindre des distances différentes (sauts). En ce qui concerne la solution pour les horizons à 1 saut, notre technique adaptative prend en compte la dynamique des nœuds et la charge du réseau. Afin d’assurer une diffusion efficace des données dans différents scénarios, la fréquence d’envoi des messages est définie en fonction des mouvements des véhicules et d’une estimation du taux de perte du réseau. Après, nous nous concentrons sur la carte des voisins jusqu’à n sauts de distance. Comme la communication avec des nœuds éloignés apporte des problèmes supplémentaires (actions de transfert, retards plus importants, informations périmées), une évaluation de confiance des nœuds identifiés et une estimation de fiabilité du chemin vers chaque voisin sont ajoutées à la carte. Au lieu d’exécuter des processus de diffusion séparés, notre troisième contribution porte sur une stratégie de coopération dont l’objectif principal est de diffuser des données tout en satisfaisant la plupart des nœuds. À cette fin, une trame unique est transmise de nœud en nœud. Sa charge utile est mise à jour localement afin qu’elle contienne les éléments de données les plus pertinents en fonction de certains critères (par exemple, urgence, pertinence). Une telle stratégie définit ainsi un horizon centré sur les données. Nous validons nos propositions au moyen d’émulations de réseaux réalistes. De toutes nos études et des résultats obtenus, nous pouvons affirmer que notre approche apporte des perspectives intéressantes pour le partage de données dans des réseaux dynamiques comme les VANET. / In the context of Intelligent Transportation Systems - ITS, vehicles may have a lot of sensors (e.g. cameras, lidars, radars) and applications (collision avoidance, traffic monitoring, etc.) generating data. They represent then an important source of information. Local applications can significantly increase their effectiveness by sharing such an information within the network. Data accuracy, confidence and pertinence can be verified when receiving data from other nodes. Therefore, we believe that an important question to answer in this context is: “How to efficiently share data within such an environment?” Data sharing is a complex task in dynamic networks. Many concerns like intermittent connections, network density variation and communication spectrum congestion arise. A usual approach to handle these problems is based on periodic processes. Indeed, a message sent many times can reach its destination even with intermittent connections and low density networks. Nevertheless, within high density networks, they may lead to communication spectrum scarcity. In this thesis we address the problem of data sharing in dynamic networks by relying in so-called horizons of pertinence. A horizon is defined as an area within which an information is expected to be received. We start focusing on data sharing within direct neighbors (at 1-hop of distance). Then we propose a solution to construct a map of neighbors, centered in the ego-node, within a horizon of n-hops. Finally, we relax the horizon definition to a dynamic defined one where different data items may reach different distances (hops). Regarding the solution for 1-hop horizons, our adaptive technique takes into account nodes’ dynamics and network load. In order to ensure an effective data dissemination in different scenarios, the sending messages frequency is defined according to vehicles movements and an estimation of the network loss rate. Following, we focus on the map of neighbors up to n-hops of distance. As communicationwith distant nodes brings additional concerns (forwarding actions, larger delays, out-of-date information), a trust evaluation of identified nodes and a reliability estimation of the multi-hop path to each neighbor is added to the map. Instead of running separated disseminating processes, our third contribution deals with a cooperative strategy with the main goal of disseminating data while satisfying most of the nodes. For this purpose a unique frame is forwarded from node to node. Its payload is locally updated so that it contains the most relevant data items according to some criteria (e.g. urgency, relevance). Such a strategy defines thus a data-centered horizon. We validate our proposals by means of realistic network emulations. From all our studies and achieved results we can state that our approach brings interesting insights for data sharing in dynamic networks like VANETs.