1,140 research outputs found

    Quality of experience and access network traffic management of HTTP adaptive video streaming

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    The thesis focuses on Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) and traffic management in access networks to improve the QoE of HAS. First, the QoE impact of adaptation parameters and time on layer was investigated with subjective crowdsourcing studies. The results were used to compute a QoE-optimal adaptation strategy for given video and network conditions. This allows video service providers to develop and benchmark improved adaptation logics for HAS. Furthermore, the thesis investigated concepts to monitor video QoE on application and network layer, which can be used by network providers in the QoE-aware traffic management cycle. Moreover, an analytic and simulative performance evaluation of QoE-aware traffic management on a bottleneck link was conducted. Finally, the thesis investigated socially-aware traffic management for HAS via Wi-Fi offloading of mobile HAS flows. A model for the distribution of public Wi-Fi hotspots and a platform for socially-aware traffic management on private home routers was presented. A simulative performance evaluation investigated the impact of Wi-Fi offloading on the QoE and energy consumption of mobile HAS.Die Doktorarbeit beschäftigt sich mit Quality of Experience (QoE) – der subjektiv empfundenen Dienstgüte – von adaptivem HTTP Videostreaming (HAS) und mit Verkehrsmanagement, das in Zugangsnetzwerken eingesetzt werden kann, um die QoE des adaptiven Videostreamings zu verbessern. Zuerst wurde der Einfluss von Adaptionsparameters und der Zeit pro Qualitätsstufe auf die QoE von adaptivem Videostreaming mittels subjektiver Crowdsourcingstudien untersucht. Die Ergebnisse wurden benutzt, um die QoE-optimale Adaptionsstrategie für gegebene Videos und Netzwerkbedingungen zu berechnen. Dies ermöglicht Dienstanbietern von Videostreaming verbesserte Adaptionsstrategien für adaptives Videostreaming zu entwerfen und zu benchmarken. Weiterhin untersuchte die Arbeit Konzepte zum Überwachen von QoE von Videostreaming in der Applikation und im Netzwerk, die von Netzwerkbetreibern im Kreislauf des QoE-bewussten Verkehrsmanagements eingesetzt werden können. Außerdem wurde eine analytische und simulative Leistungsbewertung von QoE-bewusstem Verkehrsmanagement auf einer Engpassverbindung durchgeführt. Schließlich untersuchte diese Arbeit sozialbewusstes Verkehrsmanagement für adaptives Videostreaming mittels WLAN Offloading, also dem Auslagern von mobilen Videoflüssen über WLAN Netzwerke. Es wurde ein Modell für die Verteilung von öffentlichen WLAN Zugangspunkte und eine Plattform für sozialbewusstes Verkehrsmanagement auf privaten, häuslichen WLAN Routern vorgestellt. Abschließend untersuchte eine simulative Leistungsbewertung den Einfluss von WLAN Offloading auf die QoE und den Energieverbrauch von mobilem adaptivem Videostreaming

    Hardening Tor Hidden Services

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    Tor is an overlay anonymization network that provides anonymity for clients surfing the web but also allows hosting anonymous services called hidden services. These enable whistleblowers and political activists to express their opinion and resist censorship. Administrating a hidden service is not trivial and requires extensive knowledge because Tor uses a comprehensive protocol and relies on volunteers. Meanwhile, attackers can spend significant resources to decloak them. This thesis aims to improve the security of hidden services by providing practical guidelines and a theoretical architecture. First, vulnerabilities specific to hidden services are analyzed by conducting an academic literature review. To model realistic real-world attackers, court documents are analyzed to determine their procedures. Both literature reviews classify the identified vulnerabilities into general categories. Afterward, a risk assessment process is introduced, and existing risks for hidden services and their operators are determined. The main contributions of this thesis are practical guidelines for hidden service operators and a theoretical architecture. The former provides operators with a good overview of practices to mitigate attacks. The latter is a comprehensive infrastructure that significantly increases the security of hidden services and alleviates problems in the Tor protocol. Afterward, limitations and the transfer into practice are analyzed. Finally, future research possibilities are determined

    Heterogeneous Acceleration for 5G New Radio Channel Modelling Using FPGAs and GPUs

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Transforming Large-Scale Virtualized Networks: Advancements in Latency Reduction, Availability Enhancement, and Security Fortification

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    In today’s digital age, the increasing demand for networks, driven by the proliferation of connected devices, data-intensive applications, and transformative technologies, necessitates robust and efficient network infrastructure. This thesis addresses the challenges posed by virtualization in 5G networking and focuses on enhancing next-generation Radio Access Networks (RANs), particularly Open-RAN (O-RAN). The objective is to transform virtualized networks into highly reliable, secure, and latency-aware systems. To achieve this, the thesis proposes novel strategies for virtual function placement, traffic steering, and virtual function security within O-RAN. These solutions utilize optimization techniques such as binary integer programming, mixed integer binary programming, column generation, and machine learning algorithms, including supervised learning and deep reinforcement learning. By implementing these contributions, network service providers can deploy O-RAN with enhanced reliability, speed, and security, specifically tailored for Ultra-Reliable and Low Latency Communications use cases. The optimized RAN virtualization achieved through this research unlocks a new era in network architecture that can confidently support URLLC applications, including Autonomous Vehicles, Industrial Automation and Robotics, Public Safety and Emergency Services, and Smart Grids

    Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

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    The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

    Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

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    This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book

    Near-Real Time, Semi-Automated Threat Assessment of Information Environments

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    Threat assessment is a crucial process for monitoring and defending against potential threats in an organization’s information environment and business operations. Ensuring the security of information infrastructure requires effective information security practices. However, existing models and methodologies often fall short of addressing the dynamic and evolving nature of cyberattacks. Moreover, critical threat intelligence extracted from the threat agents lacks the ability to capture essential attributes such as motivation, opportunity, and capability (M, O, C). This contribution to knowledge clarification introduces a semi-automatic threat assessment model that can handle situational awareness data or live acquired data stream from networks, incorporating information security techniques, protocols, and real-time monitoring of specific network types. Additionally, it focuses on analysing and implementing network traffic within a specific real-time information environment. To develop the semi-automatic threat assessment model, the study identifies unique attributes of threat agents by analysing Packet Capture Application Programming Interface (PCAP) files and data stream collected between 2012 and 2019. The study utilizes both hypothetical and real-world examples of threat agents to evaluate the three key factors: motivation, opportunity, and capability. This evaluation serves as a basis for designing threat profiles, critical threat intelligence, and assessing the complexity of process. These aspects are currently overlooked in existing threat agent taxonomies, models, and methodologies. By addressing the limitations of traditional threat assessment approaches, this research contributes to advancing the field of cybersecurity. The proposed semi-automatic threat assessment model offers improved awareness and timely detection of threats, providing organizations with a more robust defence against evolving cyberattacks. This research enhances the understanding of threat agents’ attributes and assists in developing proactive strategies to mitigate the risks associated with cybersecurity in the modern information environment
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