Proactive Mechanisms for Video-on-Demand Content Delivery

Video delivery over the Internet is the dominant source of network load all over the world. Especially VoD streaming services such as YouTube, Netflix, and Amazon Video have propelled the proliferation of VoD in many peoples' everyday life. VoD allows watching video from a large quantity of content at any time and on a multitude of devices, including smart TVs, laptops, and smartphones. Studies show that many people under the age of 32 grew up with VoD services and have never subscribed to a traditional cable TV service. This shift in video consumption behavior is continuing with an ever-growing number of users. satisfy this large demand, VoD service providers usually rely on CDN, which make VoD streaming scalable by operating a geographically distributed network of several hundreds of thousands of servers. Thereby, they deliver content from locations close to the users, which keeps traffic local and enables a fast playback start. CDN experience heavy utilization during the day and are usually reactive to the user demand, which is not optimal as it leads to expensive over-provisioning, to cope with traffic peaks, and overreacting content eviction that decreases the CDN's performance. However, to sustain future VoD streaming projections with hundreds of millions of users, new approaches are required to increase the content delivery efficiency. To this end, this thesis identifies three key research areas that have the potential to address the future demand for VoD content. Our first contribution is the design of vFetch, a privacy-preserving prefetching mechanism for mobile devices. It focuses explicitly on OTT VoD providers such as YouTube. vFetch learns the user interest towards different content channels and uses these insights to prefetch content on a user terminal. To do so, it continually monitors the user behavior and the device's mobile connectivity pattern, to allow for resource-efficient download scheduling. Thereby, vFetch illustrates how personalized prefetching can reduce the mobile data volume and alleviate mobile networks by offloading peak-hour traffic. Our second contribution focuses on proactive in-network caching. To this end, we present the design of the ProCache mechanism that divides the available cache storage concerning separate content categories. Thus, the available storage is allocated to these divisions based on their contribution to the overall cache efficiency. We propose a general work-flow that emphasizes multiple categories of a mixed content workload in addition to a work-flow tailored for music video content, the dominant traffic source on YouTube. Thereby, ProCache shows how content-awareness can contribute to efficient in-network caching. Our third contribution targets the application of multicast for VoD scenarios. Many users request popular VoD content with only small differences in their playback start time which offers a potential for multicast. Therefore, we present the design of the VoDCast mechanism that leverages this potential to multicast parts of popular VoD content. Thereby, VoDCast illustrates how ISP can collaborate with CDN to coordinate on content that should be delivered by ISP-internal multicast

Resilient and Scalable Forwarding for Software-Defined Networks with P4-Programmable Switches

Traditional networking devices support only fixed features and limited configurability. Network softwarization leverages programmable software and hardware platforms to remove those limitations. In this context the concept of programmable data planes allows directly to program the packet processing pipeline of networking devices and create custom control plane algorithms. This flexibility enables the design of novel networking mechanisms where the status quo struggles to meet high demands of next-generation networks like 5G, Internet of Things, cloud computing, and industry 4.0. P4 is the most popular technology to implement programmable data planes. However, programmable data planes, and in particular, the P4 technology, emerged only recently. Thus, P4 support for some well-established networking concepts is still lacking and several issues remain unsolved due to the different characteristics of programmable data planes in comparison to traditional networking. The research of this thesis focuses on two open issues of programmable data planes. First, it develops resilient and efficient forwarding mechanisms for the P4 data plane as there are no satisfying state of the art best practices yet. Second, it enables BIER in high-performance P4 data planes. BIER is a novel, scalable, and efficient transport mechanism for IP multicast traffic which has only very limited support of high-performance forwarding platforms yet. The main results of this thesis are published as 8 peer-reviewed and one post-publication peer-reviewed publication. The results cover the development of suitable resilience mechanisms for P4 data planes, the development and implementation of resilient BIER forwarding in P4, and the extensive evaluations of all developed and implemented mechanisms. Furthermore, the results contain a comprehensive P4 literature study. Two more peer-reviewed papers contain additional content that is not directly related to the main results. They implement congestion avoidance mechanisms in P4 and develop a scheduling concept to find cost-optimized load schedules based on day-ahead forecasts

Scalability and Resilience Analysis of Software-Defined Networking

Software-defined Networking (SDN) ist eine moderne Architektur für Kommunikationsnetze, welche entwickelt wurde, um die Einführung von neuen Diensten und Funktionen in Netzwerke zu erleichtern. Durch eine Trennung der Weiterleitungs- und Kontrollfunktionen sind nur wenige Kontrollelemente mit Software-Updates zu versehen, um Veränderungen am Netz vornehmen zu können. Allerdings wirft die Netzstrukturierung von SDN neue Fragen bezüglich Skalierbarkeit und Ausfallsicherheit auf, welche in dezentralen Netzstrukturen nicht auftreten. In dieser Arbeit befassen wir uns mit Fragestellungen zu Skalierbarkeit und Ausfallsicherheit in Bezug auf Unicast- und Multicast-Verkehr in SDN-basierten Netzen. Wir führen eine Komprimierungstechnik für Routingtabellen ein, welche die Skalierungsproblematik aktueller SDN Weiterleitungsgeräte verbessern soll und ermitteln ihre Effizienz in einer Leistungsbewertung. Außerdem diskutieren wir unterschiedliche Methoden, um die Ausfallsicherheit in SDN zu verbessern. Wir analysieren sie auf öffentlich zugänglichen Netzwerken und benennen Vor- und Nachteile der Ansätze. Abschließend schlagen wir eine skalierbare und ausfallsichere Architektur für Multicast-basiertes SDN vor. Wir untersuchen ihre Effizienz in einer Leistungsbewertung und zeigen ihre Umsetzbarkeit mithilfe eines Prototypen.Software-Defined Networking (SDN) is a novel architecture for communication networks that has been developed to ease the introduction of new network services and functions. It leverages the separation of the data plane and the control plane to allow network services to be deployed solely in software. Although SDN provides great flexibility, the applicability of SDN in communication networks raises several questions with regard to scalability and resilience against network failures. These concerns are not prevalent in current decentralized network architectures. In this thesis, we address scalability and resilience issues with regard to unicast and multicast traffic for SDN-based networks. We propose a new compression method for inter-domain routing tables to address hardware limitations of current SDN switches and analyze its effectiveness. We propose various resilience methods for SDN and identify their key performance indicators in the context of carrier-grade and datacenter networks. We discuss the advantages and disadvantages of these proposals and their appropriate use cases. Finally, we propose a scalable and resilient software-defined multicast architecture. We study the effectiveness of our approach and show its feasibility using a prototype implementation