Complex cyber-physical systems have become fundamental to modern society by effectively providing critical services and improving efficiency in various domains. Unfortunately, as systems become more connected and more complex, they also can become more vulnerable and less robust. As a result, various failure modes become more common and easily triggered from both unanticipated and malicious perturbations. Research has been conducted in the area of vulnerability analysis for cyber-physical systems, to assist in locating these possible vulnerabilities before they can fail. I present two case studies on different forms of critical infrastructure systems to identify vulnerabilities and understand how external perturbations can affect them, namely UAV drone swarms and municipal water infrastructure.

This dissertation focuses on the path planning of unmanned aerial vehicle (UAV) swarms under distributed and hybrid control scenarios. It presents two such models and analyzes them both from theory and practice. In the first method, a distributed formation control strategy for UAV swarm based on consensus law is presented. This model makes use of the fundamental concepts of leader-follower structure, social potential functions, and algebraic graph theory to jointly address flocking and de-confliction in the formation control problem. The impact of network topology on formation control is analyzed. It is shown that the degree distribution of the network representing the multi-agent system defines the rate at which formation is attained. Conditions for convergence and stability are derived. In the second method, a hybrid framework for path planning and coverage area by UAV swarms is presented. This strategy significantly improves the current labor-intensive and resource-constraint operations in aquaculture farms. To monitor the farms periodically, an optimized back-and-forth flight path based on the Shamos algorithm is utilized. A trajectory tracking strategy for UAV swarms under uncertain wind conditions is presented.

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The development of Unmanned Aerial Vehicles (UAVs) and fifth-generation (5G) wireless technology provides more possibilities for wireless networks. The application of UAVs is gradually evolving from individual UAVs performing tasks to UAV swarm performing tasks in concert. A UAV swarm network is when many drones work cooperatively in a swarm mode to achieve a particular goal. Due to the UAV swarm's easy deployment, self-organization, self-management, and high flexibility, it can provide robust and efficient wireless communications in some unique scenarios, such as emergency communications, hotspot region coverage, sensor networks, and vehicular networks. Therefore, UAV networks have attracted more and more attention from commercial and military; however, many problems need to be resolved before UAV cellular communications become a reality. One of the most challenging core components is the routing protocol design in the UAV swarm network. Due to the high mobility of UAVs, the position of each UAV changes dynamically, so problems such as high latency, high packet loss rate, and even loss of connection arise when UAVs are far apart. These problems dramatically reduce the transmission rate and data integrity for traditional routing protocols based on path discovery. This thesis focuses on developing, emulating, and optimizing a flooding-based routing protocol for UAV swarm using Random Linear Network Coding (RLNC) to improve the latency and bit rate and solve the packet loss problem without routing information and network topology. RLNC can reduce the number of packets demand in some hops. Due to this feature of RLNC, when relay transmitter UAVs or the destination receiver UAV receive sufficient encoded packets from any transmitter UAVs, the raw data can be decoded. For those relay transmitter UAVs in the UAV swarm network that already received some encoded packets in previous hops but not enough to decode the raw data, only need to receive the rest of the different encoded packets needed for decoding. Thus, flooding-based routing protocol significantly improves transmission efficiency in the UAV swarm network. / Master of Science / People are used to using fiber, 4G, and Wi-Fi in the city, but numerous people still live in areas without Internet access. Moreover, in some particular scenarios like large-scale activities, remote areas, and military operations, when the cellular network cannot provide enough bandwidth or good signal, UAV wireless network would be helpful and provide stable Internet access. Successful UAV test flights can last for several weeks, and researchers' interest in high-altitude long-endurance (HALE) UAVs are booming. HALE UAVs will create Wi-Fi or other network signals for remote areas, including polar regions, which will allow millions of people to enter the information society and connect to the Internet. The development of UAV and 5G provides more possibilities for wireless networks. UAV applications have evolved from individual UAV performing tasks to UAV swarm performing tasks. A UAV swarm network is where multiple drones work in tandem to achieve a particular goal. It can provide robust and efficient wireless communications in unique scenarios. As a result, UAVs are receiving attention from both commercial and military. However, there are still many problems that need to be resolved before the actual use of UAVs. One of the biggest challenges is routing protocol which is how UAVs communicate with each other and select routes. As the location of UAVs is constantly changing, this leads to delays, data loss, or complete loss of connectivity. Ultimately these issues can lead to slow transmission speed and lack of data integrity for traditional routing protocols based on path discovery. This thesis focuses on developing, emulating, and optimizing a flooding-based routing protocol for the UAV swarm. Specifically, this protocol uses RLNC, which can reduce the number of packets demand in some hops so that the latency and transmission speed will be improved, and the data loss problem will also be solved. Due to this feature of RLNC, when any receiver receives enough encoded packets from any transmitter, the original data can be decoded. Some receivers that already received some encoded packets in the previous transmission only need to receive the rest of the different encoded packets needed for decoding. Therefore, flooding-based routing protocol significantly improves transmission efficiency for UAV swarm networks.

Les travaux présentés dans cette thèse effectuée au LaBRI portent sur la mise en place d’une flotte de drones et le portage sur celle-ci d’applications collaboratives distribuées utilisant des communications asynchrones non sûres. Ces applications sont formalisées grâce au modèle de réétiquetage de graphes Asynchronous Dynamicity Aware Graph Relabeling System (ADAGRS) que nous proposons. Au delà des contributions théoriques, ces travaux ont débouché sur la mise en place du démonstrateur CARUS dans lequel cinq drones se partagent la surveillance d'une grille de 15 points d’incidents potentiels (au sol).Lorsqu’un drone détecte un incident, il s'en rapproche pour le traiter. Le reste de la flotte doit alors prendre en charge les points que ce drone ne traite plus.Les réorganisations nécessaires de la flotte se font en totale autonomie vis-à-vis du sol et sous hypothèse de perte éventuelle de drones et de messages. / The work presented in this thesis, carried out at LaBRI, deals with the set up of a fleet of UAVs and the porting on it of distributed collaborative applications that use unsafe asynchronous communications. These applications are modeled with Asynchronous Dynamicity Aware Graph Relabeling System (ADAGRS), the formal model based on graph relabellings that we propose.Beyond the theoretical contributions, this work led to the development of the CARUS demonstrator in which five UAVs share the supervision of a grid of 15 points of potential ground incidents.When a UAV detects an incident, it comes close to it in order to deal with it. The rest of the fleet must then take care of the points that this UAV no longer visits.The necessary reorganizations of the fleet are done in total autonomy with respect to the ground and under the hypothesis of possible loss of UAVs and messages.