Efficient Multi-Hop Communications for Software-Defined Wireless Networks

PhD thesisSoftware-Defined Networking (SDN) recently emerged to overcome the difficulty of network control by decoupling the control plane from the data plane. In terms of the wireless medium and mobile devices, although new challenges are introduced into SDN research, SDN promises to address many inherited problems in wireless communication networks. However, centralised SDN control brings concerns of scalability, reliability, and robustness especially for wireless networks. Considering these concerns, the use of physically distributed SDN controllers has been recognized as an effective solution. Nevertheless, it remains a challenge in regard to how the physically distributed controllers effectively communicate to form a logically centralised network control plane. Dissemination is a type of one-to-many communication service which plays an important role in control information exchange. This research focuses on the strategic packet forwarding for more efficient multi-hop communications in software-defined wireless networks. The research aim is to improve the delivery efficiency by exploiting the delay budget and node mobility. To achieve this objective, existing multi-hop forwarding methods and dissemination schemes in wireless networks are investigated and analysed. In the literature, information from the navigation system of mobile nodes has been utilised to identify candidate relay nodes. However, further studies are required to utilise partially predictable mobility based on more generalised navigational information such as the movement direction. In this research, the feasible exploitation of directional movement in path-unconstrained mobility is investigated for efficient multi-hop communications. Simulation results show that the proposed scheme outperforms the state-of-the-art because directional correlation of node movement is considered to dynamically exploit the delay budget for better selection of the relay node(s).Chinese Scholarship Council (CSC

Mobile Edge Computing

This is an open access book. It offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks. The book starts with the basic concepts, key techniques and network architectures of MEC. Then, we present the wide applications of MEC, including edge caching, 6G networks, Internet of Vehicles, and UAVs. In the last part, we present new opportunities when MEC meets blockchain, Artificial Intelligence, and distributed machine learning (e.g., federated learning). We also identify the emerging applications of MEC in pandemic, industrial Internet of Things and disaster management. The book allows an easy cross-reference owing to the broad coverage on both the principle and applications of MEC. The book is written for people interested in communications and computer networks at all levels. The primary audience includes senior undergraduates, postgraduates, educators, scientists, researchers, developers, engineers, innovators and research strategists

Contributions to Vehicular Communications Systems and Schemes

La dernière décennie a marqué une grande hausse des applications véhiculaires comme une nouvelle source de revenus et un facteur de distinction dans l'industrie des véhicules. Ces applications véhiculaires sont classées en deux groupes : les applications de sécurité et les applications d'info divertissement. Le premier groupe inclue le changement intelligent de voie, l'avertissement de dangers de routes et la prévention coopérative de collision qui comprend la vidéo sur demande (VoD), la diffusion en direct, la diffusion de météo et de nouvelles et les jeux interactifs. Cependant, Il est à noter que d'une part, les applications véhiculaires d'info divertissement nécessitent une bande passante élevée et une latence relativement faible ; D'autre part, les applications de sécurité requièrent exigent un délai de bout en bout très bas et un canal de communication fiable pour la livraison des messages d'urgence. Pour satisfaire le besoin en applications efficaces, les fabricants de véhicules ainsi que la communauté académique ont introduit plusieurs applications à l’intérieur de véhicule et entre véhicule et véhicule (V2V). Sauf que, l'infrastructure du réseau sans fil n'a pas été conçue pour gérer les applications de véhicules, en raison de la haute mobilité des véhicules, de l'imprévisibilité du comportement des conducteurs et des modèles de trafic dynamiques. La relève est l'un des principaux défis des réseaux de véhicules, car la haute mobilité exige au réseau sans fil de faire la relève en un très court temps. De plus, l'imprévisibilité du comportement du conducteur cause l'échec des protocoles proactifs traditionnels de relève, car la prédiction du prochain routeur peut changer en fonction de la décision du conducteur. Aussi, le réseau de véhicules peut subir une mauvaise qualité de service dans les régions de relève en raison d'obstacles naturels, de véhicules de grande taille ou de mauvaises conditions météorologiques. Cette thèse se concentre sur la relève dans l'environnement des véhicules et son effet sur les applications véhiculaires. Nous proposons des solutions pratiques pour les réseaux actuellement déployés, principalement les réseaux LTE, l'infrastructure véhicule à véhicule (V2V) ainsi que les outils efficaces d’émulateurs de relèves dans les réseaux véhiculaires.----------ABSTRACT: The last decade marked the rise of vehicular applications as a new source of revenue and a key differentiator in the vehicular industry. Vehicular Applications are classified into safety and infotainment applications. The former include smart lane change, road hazard warning, and cooperative collision avoidance; however, the latter include Video on Demand (VoD), live streaming, weather and news broadcast, and interactive games. On one hand, infotainment vehicular applications require high bandwidth and relatively low latency; on the other hand, safety applications requires a very low end to end delay and a reliable communication channel to deliver emergency messages. To satisfy the thirst for practical applications, vehicle manufacturers along with research institutes introduced several in-vehicle and Vehicle to Vehicle (V2V) applications. However, the wireless network infrastructure was not designed to handle vehicular applications, due to the high mobility of vehicles, unpredictability of drivers’ behavior, and dynamic traffic patterns. Handoff is one of the main challenges of vehicular networks since the high mobility puts pressure on the wireless network to finish the handoff within a short period. Moreover, the unpredictability of driver behavior causes the traditional proactive handoff protocols to fail, since the prediction of the next router may change based on the driver’s decision. Moreover, the vehicular network may suffer from bad Quality of Service (QoS) in the regions of handoff due to natural obstacles, large vehicles, or weather conditions. This thesis focuses on the handoff on the vehicular environment and its effect on the vehicular applications. We consider practical solutions for the currently deployed networks mainly Long Term Evolution (LTE) networks, the Vehicle to Vehicle (V2V) infrastructure, and the tools that can be used effectively to emulate handoff on the vehicular networks

An Approach to Guide Users Towards Less Revealing Internet Browsers

When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Previous research has shown that there are numerous privacy and security risks result from exposing sensitive information in the User-Agent string. For example, it enables device and browser fingerprinting and user tracking and identification. Our large analysis of thousands of User-Agent strings shows that browsers differ tremendously in the amount of information they include in their User-Agent strings. As such, our work aims at guiding users towards using less exposing browsers. In doing so, we propose to assign an exposure score to browsers based on the information they expose and vulnerability records. Thus, our contribution in this work is as follows: first, provide a full implementation that is ready to be deployed and used by users. Second, conduct a user study to identify the effectiveness and limitations of our proposed approach. Our implementation is based on using more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available and the solution has been deployed

Artificial Intelligence and Cybersecurity: Building an Automotive Cybersecurity Framework Using Machine Learning Algorithms

Automotive technology has continued to advance in many aspects. As an outcome of such advancements, autonomous vehicles are closer to commercialization and have brought to life a complex automotive technology ecosystem [1]. Like every other technology, these developments bring benefits but also introduce a variety of risks. One of these risks in the automotive space is cybersecurity threats. In the case of cars, these security challenges can produce devastating results and tremendous costs, including loss of life. Therefore, conducting a clear analysis, assessment and detection of threats solves some of the cybersecurity challenges in the automotive ecosystem. This dissertation does just that, by building a three-step framework to analyze, assess,and detect threats using machine learning algorithms. First, it does an analysis of the connected vehicle threats while leveraging the STRIDE framework [2]. Second, it presents an innovative, Fuzzy based threat assessment model (FTAM). FTAM leverages threat characterizations from established threat assessment models while focusing on improving its assessment capabilities by using Fuzzy logic. Through this methodology, FTAM can improve the efficiency and accuracy of the threat assessment process by using Fuzzy logic to determine the “degree” of the threat over other existing methods. This differs from the current threat assessment models which use subjective assessment processes based on table look-ups or scoring. Thirdly, this dissertation proposes an intrusion detection system (IDS) to detect malicious threats while taking in consideration results from the previous assessment stage. This IDS uses the dataset provided from Wyoming Connected Vehicle Deployment program [3] and consists of a two-stage intrusion detection system based on supervised and unsupervised machine learning algorithms. The first stage uses unsupervised learning to detect whether there is an attack present and the second stage classifies these attacks in a supervised learning fashion. The second stage also addresses data bias and eliminates the number of false positives. The simulation of this approach results in an IDS able to detect and classify attacks at a 99.965% accuracy and lowers the false positives rate to 0%.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/149467/1/Nevrus Kaja PhD Dissertation V24.pdfDescription of Nevrus Kaja PhD Dissertation V24.pdf : Dissertatio

Scaling Laws for Vehicular Networks

Equipping automobiles with wireless communications and networking capabilities is becoming the frontier in the evolution to the next generation intelligent transportation systems (ITS). By means of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, information generated by the vehicle-borne computer, vehicle control system, on-board sensors, or roadside infrastructure, can be effectively disseminated among vehicles/infrastructure in proximity or to vehicles/infrastructure multiple hops away, known as vehicular networks (VANETs), to enhance the situational awareness of vehicles and provide motorist/passengers with an information-rich travel environment. Scaling law for throughput capacity and delay in wireless networks has been considered as one of the most fundamental issues, which characterizes the trend of throughput/delay behavior when the network size increases. The study of scaling laws can lead to a better understanding of intrinsic properties of wireless networks and theoretical guidance on network design and deployment. Moreover, the results could also be applied to predict network performance, especially for the large-scale vehicular networks. However, map-restricted mobility and spatio-temporal dynamics of vehicle density dramatically complicate scaling laws studies for VANETs. As an effort to lay a scientific foundation of vehicular networking, my thesis investigates capacity scaling laws for vehicular networks with and without infrastructure, respectively. Firstly, the thesis studies scaling law of throughput capacity and end-to-end delay for a social-proximity vehicular network, where each vehicle has a restricted mobility region around a specific social spot and services are delivered in a store-carry-and-forward paradigm. It has been shown that although the throughput and delay may degrade in a high vehicle density area, it is still possible to achieve almost constant scaling for per vehicle throughput and end-to-end delay. Secondly, in addition to pure ad hoc vehicular networks, the thesis derives the capacity scaling laws for networks with wireless infrastructure, where services are delivered uniformly from infrastructure to all vehicles in the network. The V2V communication is also required to relay the downlink traffic to the vehicles outside the coverage of infrastructure. Three kinds of infrastructures have been considered, i.e., cellular base stations, wireless mesh backbones (a network of mesh nodes, including one mesh gateway), and roadside access points. The downlink capacity scaling is derived for each kind of infrastructure. Considering that the deployment/operation costs of different infrastructure are highly variable, the capacity-cost tradeoffs of different deployments are examined. The results from the thesis demonstrate the feasibility of deploying non-cellular infrastructure for supporting high-bandwidth vehicular applications. Thirdly, the fundamental impact of traffic signals at road intersection on drive-thru Internet access is particularly studied. The thesis analyzes the time-average throughput capacity of a typical vehicle driving through randomly deployed roadside Wi-Fi networks. Interestingly, we show a significant throughput gain for vehicles stopping at intersections due to red signals. The results provide a quick and efficient way of determining the Wi-Fi deployment scale according to required quality of services. In summary, the analysis developed and the scaling laws derived in the thesis provide should be very useful for understanding the fundamental performance of vehicular networks

VANET-enabled eco-friendly road characteristics-aware routing for vehicular traffic

There is growing awareness of the dangers of climate change caused by greenhouse gases. In the coming decades this could result in numerous disasters such as heat-waves, flooding and crop failures. A major contributor to the total amount of greenhouse gas emissions is the transport sector, particularly private vehicles. Traffic congestion involving private vehicles also causes a lot of wasted time and stress to commuters. At the same time new wireless technologies such as Vehicular Ad-Hoc Networks (VANETs) are being developed which could allow vehicles to communicate with each other. These could enable a number of innovative schemes to reduce traffic congestion and greenhouse gas emissions. 1) EcoTrec is a VANET-based system which allows vehicles to exchange messages regarding traffic congestion and road conditions, such as roughness and gradient. Each vehicle uses the messages it has received to build a model of nearby roads and the traffic on them. The EcoTrec Algorithm then recommends the most fuel efficient route for the vehicles to follow. 2) Time-Ants is a swarm based algorithm that considers not only the amount of cars in the spatial domain but also the amoumt in the time domain. This allows the system to build a model of the traffic congestion throughout the day. As traffic patterns are broadly similar for weekdays this gives us a good idea of what traffic will be like allowing us to route the vehicles more efficiently using the Time-Ants Algorithm. 3) Electric Vehicle enhanced Dedicated Bus Lanes (E-DBL) proposes allowing electric vehicles onto the bus lanes. Such an approach could allow a reduction in traffic congestion on the regular lanes without greatly impeding the buses. It would also encourage uptake of electric vehicles. 4) A comprehensive survey of issues associated with communication centred traffic management systems was carried out

Security of Cyber-Physical Systems

Cyber-physical system (CPS) innovations, in conjunction with their sibling computational and technological advancements, have positively impacted our society, leading to the establishment of new horizons of service excellence in a variety of applicational fields. With the rapid increase in the application of CPSs in safety-critical infrastructures, their safety and security are the top priorities of next-generation designs. The extent of potential consequences of CPS insecurity is large enough to ensure that CPS security is one of the core elements of the CPS research agenda. Faults, failures, and cyber-physical attacks lead to variations in the dynamics of CPSs and cause the instability and malfunction of normal operations. This reprint discusses the existing vulnerabilities and focuses on detection, prevention, and compensation techniques to improve the security of safety-critical systems

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering