The State of Network Neutrality Regulation

The Network Neutrality (NN) debate refers to the battle over the design of a regulatory framework for preserving the Internet as a public network and open innovation platform. Fueled by concerns that broadband access service providers might abuse network management to discriminate against third party providers (e.g., content or application providers), policymakers have struggled with designing rules that would protect the Internet from unreasonable network management practices. In this article, we provide an overview of the history of the debate in the U.S. and the EU and highlight the challenges that will confront network engineers designing and operating networks as the debate continues to evolve.BMBF, 16DII111, Verbundprojekt: Weizenbaum-Institut für die vernetzte Gesellschaft - Das Deutsche Internet-Institut; Teilvorhaben: Wissenschaftszentrum Berlin für Sozialforschung (WZB)EC/H2020/679158/EU/Resolving the Tussle in the Internet: Mapping, Architecture, and Policy Making/ResolutioNe

Value Creation in a QoE Environment

User behavior of multimedia services currently undergoes strong changes. This is reflected in several recent trends, e.g. the increase of rich media content consumption, preferences for more individual and personalized services and the higher sensitivity of end users for quality issues. These changes will eventually lead to strong changes in network traffic characteristics: rising congestion in peak times and less availability of bandwidth for the individual user. As a result, the quality as perceived by the end-user will decrease if network operators and service providers do not anticipate the required changes for the network. Measurable network requirements such as available video and speech quality, security and reliability are addressed by technologies that are commonly summed up in the Quality of Service (QoS) concept. However, the end-users' perception of quality is only reflected in the wider concept of Quality of Experience (QoE). This takes the measurable network requirements into account as well as customer needs, wants and preferences. For the implementation of QoE technologies several network components need to be added or changed resulting in high capital expenditures. Yet, it is not clear if these costs can be compensated with efficiency increases. Thus, new revenue streams for the network operator are necessary to incentivize investments in QoE technologies. In this paper we address four new value creation models that can serve as basis for more elaborated business models for network operators and other actors. We show how interest in QoE of the user, the content provider, the service provider and the advertiser induces new revenue streams. These models are embedded in five possible future QoE scenarios that reveal regulation, end user quality sensibility and end-to-end support as major issues for the future. --Business Models,Quality of Experience (QoE),Quality of Service (QoS),Value Creation

Quality of Service improvements for real time multimedia applications using next generation network architectures and blockchain in Internet Service Provider cooperative scenario

Real time communications are becoming part of our daily life, requiring constrained requisites with the purpose of being enjoyed in harmony by end users. The factors ruling these requisites are Quality of Service parameters of the users' Internet connections. Achieving a satisfactory QoS level for real time communications depends on parameters that are strongly influenced by the quality of the network connections among the Internet Service Providers, which are located in the path between final users and Over The Top service providers that are supplying them with real time services. Final users can be: business people having real time videoconferences, or adopting crytpocurrencies in their exchanges, videogamers playing online games together with others residing in other countries, migrants talking with their relatives or watching their children growing up in their home countries, people with disabilities adopting tecnologies to help them, doctors performing remote surgeries, manufacturers adopting augmented reality devices to perform dangerous tasks. Each of them performing their daily activities are requiring specific QoS parameters to their ISPs, that nowadays seem to be unable to provide them with a satisfactory QoS level for these kinds of real time services. Through the adoption of next generation networks, such as the Information Centric Networking, it would be possible to overcome the QoS problems that nowadays are experienced. By adopting Blockchain technologies, in several use cases, it would be possible to improve those security aspects related to the non-temperability of information and privacy. I started this thesis analyzing next generation architectures enabling real time multimedia communications. In Software Defined Networking, Named Data Networking and Community Information Centric Networking, I highlighted potential approaches to solve QoS problems that are affecting real time multimedia applications. During my experiments I found that applications able to transmit high quality videos, such as 4k or 8k videos, or to directly interact with devices AR/VR enabled are missing for both ICN approaches. Then I proposed a REST interface for the enforcing of a specific QoS parameter, the round trip time (RTT) taking into consideration the specific use case of a game company that connects with the same telecommunication company of the final user. Supposing that the proposed REST APIs have been deployed in the game company and in the ISP, when one or more users are experiencing lag, the game company will try to ask the ISP to reduce the RTT for that specific user or that group of users. This request can be done by performing a call to a method where IP address(es) and the maximum RTT desired are passed. I also proposed other methods, through which it would be possible to retrieve information about the QoS parameters, and exchange, if necessary, an exceeding parameter in change of another one. The proposed REST APIs can also be used in more complex scenarios, where ISPs along the path are chained together, in order to improve the end to end QoS among Over The Top service provider and final users. To store the information exchanged by using the proposed REST APIs, I proposed to adopt a permissioned blockchain, analizying the ISPs cooperative use case with Hyperledger Fabric, where I proposed the adoption of the Proof of Authority consensus algorithm, to increase the throughput in terms of transactions per second. In a specific case that I examined, I am proposing a combination of Information Centric Networking and Blockchain, in an architecture where ISPs are exchanging valuable information regarding final Users, to improve their QoS parameters. I also proposed my smart contract for the gaming delay use case, that can be used to rule the communication among those ISPs that are along the path among OTT and final users. An extension of this work can be done, by defining billing costs for the QoS improvements

Quality of Experience monitoring and management strategies for future smart networks

One of the major driving forces of the service and network's provider market is the user's perceived service quality and expectations, which are referred to as user's Quality of Experience (QoE). It is evident that QoE is particularly critical for network providers, who are challenged with the multimedia engineering problems (e.g. processing, compression) typical of traditional networks. They need to have the right QoE monitoring and management mechanisms to have a significant impact on their budget (e.g. by reducing the users‘ churn). Moreover, due to the rapid growth of mobile networks and multimedia services, it is crucial for Internet Service Providers (ISPs) to accurately monitor and manage the QoE for the delivered services and at the same time keep the computational resources and the power consumption at low levels. The objective of this thesis is to investigate the issue of QoE monitoring and management for future networks. This research, developed during the PhD programme, aims to describe the State-of-the-Art and the concept of Virtual Probes (vProbes). Then, I proposed a QoE monitoring and management solution, two Agent-based solutions for QoE monitoring in LTE-Advanced networks, a QoE monitoring solution for multimedia services in 5G networks and an SDN-based approach for QoE management of multimedia services

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

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

mPlane: an intelligent measurement plane for the internet

The Internet's universality is based on its decentralization and diversity. However, its distributed nature leads to operational brittleness and difficulty in identifying the root causes of performance and availability issues, especially when the involved systems span multiple administrative domains. The first step to address this fragmentation is coordinated measurement: we propose to complement the current Internet's data and control planes with a measurement plane, or mPlane for short. mPlane's distributed measurement infrastructure collects and analyzes traffic measurements at a wide variety of scales to monitor the network status. Its architecture is centered on a flexible control interface, allowing the incorporation of existing measurement tools through lightweight mPlane proxy components, and offering dynamic support for new capabilities. A focus on automated, iterative measurement makes the platform well-suited to troubleshooting support. This is supported by a reasoning system, which applies machine learning algorithms to learn from success and failure in drilling down to the root cause of a problem. This article describes the mPlane architecture and shows its applicability to several distributed measurement problems involving content delivery networks and Internet service roviders. A first case study presents the tracking and iterative analysis of cache selection policies in Akamai, while a second example focuses on the cooperation between Internet service providers and content delivery networks to better orchestrate their traffic engineering decisions and jointly improve their performance