Resilient Distributed Optimization Algorithms for Resource Allocation

Distributed algorithms provide flexibility over centralized algorithms for resource allocation problems, e.g., cyber-physical systems. However, the distributed nature of these algorithms often makes the systems susceptible to man-in-the-middle attacks, especially when messages are transmitted between price-taking agents and a central coordinator. We propose a resilient strategy for distributed algorithms under the framework of primal-dual distributed optimization. We formulate a robust optimization model that accounts for Byzantine attacks on the communication channels between agents and coordinator. We propose a resilient primal-dual algorithm using state-of-the-art robust statistics methods. The proposed algorithm is shown to converge to a neighborhood of the robust optimization model, where the neighborhood's radius is proportional to the fraction of attacked channels.Comment: 15 pages, 1 figure, accepted to CDC 201

Smart Traffic Operation: from Human-Driven Cars to Mixed Vehicle Autonomy

The goal of my research is to enhance urban mobility by developing reliable and efficient traffic control and management strategies. As cities grow everywhere, and urban roadways become overburdened, the need for the development of such strategies becomes more evident. With the prevalence of smart sensing devices, such as smart phones and smart intersections, cities are becoming smart. Moreover, with the emergence of new and inevitable technologies, such as autonomous and connected vehicles, electric vehicles, and mobility on demand systems, smart cities are rapidly evolving. As we experience the arrival of such technologies, there is an opportunity to reclaim urban mobility. However, a blind utilization of these technologies may deflect us from reaching this goal. In this dissertation, we study the efficient operation of smart cities via management strategies that can guarantee overall societal benefits both in the cities of today and future.We focus on two natural instances of this agenda. In the first part, we tackle some of the existing challenges in the smart operation of traffic networks which are solely shared by human-driven cars. If all vehicles are human-driven, there is room for improving the efficiency of traffic networks by appropriate coordination and control of traffic signal lights. For these networks, we develop signal control algorithms that are capable of minimizing the number of stop-and-go movements, encoding fairness among vehicular arrivals, and are robust to the knowledge of system parameters. In the second part, we analyze fundamentals of traffic networks with mixed vehicle autonomy, where both human-driven and autonomous cars coexist on roadways. We study the mobility implications of selfish autonomy, i.e. autonomous cars that are not concerned about their overall impact and simply attempt to optimize their own travel benefits. Having shown the negative consequences that the increased deployment of selfish autonomy may have, we develop a pricing mechanism which can guarantee the overall societal-scale efficiency of traffic networks with mixed vehicle autonomy. Finally, we show how autonomy can act altruistically, i.e. by taking into account the decision making process of humans, autonomous cars can potentially plan for their actions in the favor of the overall good

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

Prediction and optimization techniques for performance enhancement of vehicular ad-hoc networks

Imperial Users onl

Optimization and Communication in UAV Networks

UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects

Machine Learning for Unmanned Aerial System (UAS) Networking

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex missions simultaneously. However, the limitations of the conventional approaches are still a big challenge to make a trade-off between the massive management and efficient networking on a large scale. With 5G NR and machine learning, in this dissertation, my contributions can be summarized as the following: I proposed a novel Optimized Ad-hoc On-demand Distance Vector (OAODV) routing protocol to improve the throughput of Intra UAS networking. The novel routing protocol can reduce the system overhead and be efficient. To improve the security, I proposed a blockchain scheme to mitigate the malicious basestations for cellular connected UAS networking and a proof-of-traffic (PoT) to improve the efficiency of blockchain for UAS networking on a large scale. Inspired by the biological cell paradigm, I proposed the cell wall routing protocols for heterogeneous UAS networking. With 5G NR, the inter connections between UAS networking can strengthen the throughput and elasticity of UAS networking. With machine learning, the routing schedulings for intra- and inter- UAS networking can enhance the throughput of UAS networking on a large scale. The inter UAS networking can achieve the max-min throughput globally edge coloring. I leveraged the upper and lower bound to accelerate the optimization of edge coloring. This dissertation paves a way regarding UAS networking in the integration of CPS and machine learning. The UAS networking can achieve outstanding performance in a decentralized architecture. Concurrently, this dissertation gives insights into UAS networking on a large scale. These are fundamental to integrating UAS and National Aerial System (NAS), critical to aviation in the operated and unmanned fields. The dissertation provides novel approaches for the promotion of UAS networking on a large scale. The proposed approaches extend the state-of-the-art of UAS networking in a decentralized architecture. All the alterations can contribute to the establishment of UAS networking with CPS

Contention techniques for opportunistic communication in wireless mesh networks

Auf dem Gebiet der drahtlosen Kommunikation und insbesondere auf den tieferen Netzwerkschichten sind gewaltige Fortschritte zu verzeichnen. Innovative Konzepte und Technologien auf der physikalischen Schicht (PHY) gehen dabei zeitnah in zelluläre Netze ein. Drahtlose Maschennetzwerke (WMNs) können mit diesem Innovationstempo nicht mithalten. Die Mehrnutzer-Kommunikation ist ein Grundpfeiler vieler angewandter PHY Technologien, die sich in WMNs nur ungenügend auf die etablierte Schichtenarchitektur abbilden lässt. Insbesondere ist das Problem des Scheduling in WMNs inhärent komplex. Erstaunlicherweise ist der Mehrfachzugriff mit Trägerprüfung (CSMA) in WMNs asymptotisch optimal obwohl das Verfahren eine geringe Durchführungskomplexität aufweist. Daher stellt sich die Frage, in welcher Weise das dem CSMA zugrunde liegende Konzept des konkurrierenden Wettbewerbs (engl. Contention) für die Integration innovativer PHY Technologien verwendet werden kann. Opportunistische Kommunikation ist eine Technik, die die inhärenten Besonderheiten des drahtlosen Kanals ausnutzt. In der vorliegenden Dissertation werden CSMA-basierte Protokolle für die opportunistische Kommunikation in WMNs entwickelt und evaluiert. Es werden dabei opportunistisches Routing (OR) im zustandslosen Kanal und opportunistisches Scheduling (OS) im zustandsbehafteten Kanal betrachtet. Ziel ist es, den Durchsatz von elastischen Paketflüssen gerecht zu maximieren. Es werden Modelle für Überlastkontrolle, Routing und konkurrenzbasierte opportunistische Kommunikation vorgestellt. Am Beispiel von IEEE 802.11 wird illustriert, wie der schichtübergreifende Entwurf in einem Netzwerksimulator prototypisch implementiert werden kann. Auf Grundlage der Evaluationsresultate kann der Schluss gezogen werden, dass die opportunistische Kommunikation konkurrenzbasiert realisierbar ist. Darüber hinaus steigern die vorgestellten Protokolle den Durchsatz im Vergleich zu etablierten Lösungen wie etwa DCF, DSR, ExOR, RBAR und ETT.In the field of wireless communication, a tremendous progress can be observed especially at the lower layers. Innovative physical layer (PHY) concepts and technologies can be rapidly assimilated in cellular networks. Wireless mesh networks (WMNs), on the other hand, cannot keep up with the speed of innovation at the PHY due to their flat and decentralized architecture. Many innovative PHY technologies rely on multi-user communication, so that the established abstraction of the network stack does not work well for WMNs. The scheduling problem in WMNs is inherent complex. Surprisingly, carrier sense multiple access (CSMA) in WMNs is asymptotically utility-optimal even though it has a low computational complexity and does not involve message exchange. Hence, the question arises whether CSMA and the underlying concept of contention allows for the assimilation of advanced PHY technologies into WMNs. In this thesis, we design and evaluate contention protocols based on CSMA for opportunistic communication in WMNs. Opportunistic communication is a technique that relies on multi-user diversity in order to exploit the inherent characteristics of the wireless channel. In particular, we consider opportunistic routing (OR) and opportunistic scheduling (OS) in memoryless and slow fading channels, respectively. We present models for congestion control, routing and contention-based opportunistic communication in WMNs in order to maximize both throughput and fairness of elastic unicast traffic flows. At the instance of IEEE 802.11, we illustrate how the cross-layer algorithms can be implemented within a network simulator prototype. Our evaluation results lead to the conclusion that contention-based opportunistic communication is feasible. Furthermore, the proposed protocols increase both throughput and fairness in comparison to state-of-the-art approaches like DCF, DSR, ExOR, RBAR and ETT