Best effort measurement based congestion control

Abstract available: p.

Improving video streaming experience through network measurements and analysis

Multimedia traffic dominates today’s Internet. In particular, the most prevalent traffic carried over wired and wireless networks is video. Most popular streaming providers (e.g. Netflix, Youtube) utilise HTTP adaptive streaming (HAS) for video content delivery to end-users. The power of HAS lies in the ability to change video quality in real time depending on the current state of the network (i.e. available network resources). The main goal of HAS algorithms is to maximise video quality while minimising re-buffering events and switching between different qualities. However, these requirements are opposite in nature, so striking a perfect blend is challenging, as there is no single widely accepted metric that captures user experience based on the aforementioned requirements. In recent years, researchers have put a lot of effort into designing subjectively validated metrics that can be used to map quality, re-buffering and switching behaviour of HAS players to the overall user experience (i.e. video QoE). This thesis demonstrates how data analysis can contribute in improving video QoE. One of the main characteristics of mobile networks is frequent throughput fluctuations. There are various underlying factors that contribute to this behaviour, including rapid changes in the radio channel conditions, system load and interaction between feedback loops at the different time scales. These fluctuations highlight the challenge to achieve a high video user experience. In this thesis, we tackle this issue by exploring the possibility of throughput prediction in cellular networks. The need for better throughput prediction comes from data-based evidence that standard throughput estimation techniques (e.g. exponential moving average) exhibit low prediction accuracy. Cellular networks deploy opportunistic exponential scheduling algorithms (i.e. proportional-fair) for resource allocation among mobile users/devices. These algorithms take into account a user’s physical layer information together with throughput demand. While the algorithm itself is proprietary to the manufacturer, physical layer and throughput information are exchanged between devices and base stations. Availability of this information allows for a data-driven approach for throughput prediction. This thesis utilises a machine-learning approach to predict available throughput based on measurements in the near past. As a result, a prediction accuracy with an error less than 15% in 90% of samples is achieved. Adding information from other devices served by the same base station (network-based information) further improves accuracy while lessening the need for a large history (i.e. how far to look into the past). Finally, the throughput prediction technique is incorporated to state-of-the-art HAS algorithms. The approach is validated in a commercial cellular network and on a stock mobile device. As a result, better throughput prediction helps in improving user experience up to 33%, while minimising re-buffering events by up to 85%. In contrast to wireless networks, channel characteristics of the wired medium are more stable, resulting in less prominent throughput variations. However, all traffic traverses through network queues (i.e. a router or switch), unlike in cellular networks where each user gets a dedicated queue at the base station. Furthermore, network operators usually deploy a simple first-in-first-out queuing discipline at queues. As a result, traffic can experience excessive delays due to the large queue sizes, usually deployed in order to minimise packet loss and maximise throughput. This effect, also known as bufferbloat, negatively impacts delay-sensitive applications, such as web browsing and voice. While there exist guidelines for modelling queue size, there is no work analysing its impact on video streaming traffic generated by multiple users. To answer this question, the performance of multiple videos clients sharing a bottleneck link is analysed. Moreover, the analysis is extended to a realistic case including heterogeneous round-trip-time (RTT) and traffic (i.e. web browsing). Based on experimental results, a simple two queue discipline is proposed for scheduling heterogeneous traffic by taking into account application characteristics. As a result, compared to the state-of-the-art Active Queue Management (AQM) discipline, Controlled Delay Management (CoDel), the proposed discipline decreases median Page Loading Time (PLT) of web traffic by up to 80% compared to CoDel, with no significant negative impact on video QoE

A cross-layer middleware architecture for time and safety critical applications in MANETs

Mobile Ad hoc Networks (MANETs) can be deployed instantaneously and adaptively, making them highly suitable to military, medical and disaster-response scenarios. Using real-time applications for provision of instantaneous and dependable communications, media streaming, and device control in these scenarios is a growing research field. Realising timing requirements in packet delivery is essential to safety-critical real-time applications that are both delay- and loss-sensitive. Safety of these applications is compromised by packet loss, both on the network and by the applications themselves that will drop packets exceeding delay bounds. However, the provision of this required Quality of Service (QoS) must overcome issues relating to the lack of reliable existing infrastructure, conservation of safety-certified functionality. It must also overcome issues relating to the layer-2 dynamics with causal factors including hidden transmitters and fading channels. This thesis proposes that bounded maximum delay and safety-critical application support can be achieved by using cross-layer middleware. Such an approach benefits from the use of established protocols without requiring modifications to safety-certified ones. This research proposes ROAM: a novel, adaptive and scalable cross-layer Real-time Optimising Ad hoc Middleware framework for the provision and maintenance of performance guarantees in self-configuring MANETs. The ROAM framework is designed to be scalable to new optimisers and MANET protocols and requires no modifications of protocol functionality. Four original contributions are proposed: (1) ROAM, a middleware entity abstracts information from the protocol stack using application programming interfaces (APIs) and that implements optimisers to monitor and autonomously tune conditions at protocol layers in response to dynamic network conditions. The cross-layer approach is MANET protocol generic, using minimal imposition on the protocol stack, without protocol modification requirements. (2) A horizontal handoff optimiser that responds to time-varying link quality to ensure optimal and most robust channel usage. (3) A distributed contention reduction optimiser that reduces channel contention and related delay, in response to detection of the presence of a hidden transmitter. (4) A feasibility evaluation of the ROAM architecture to bound maximum delay and jitter in a comprehensive range of ns2-MIRACLE simulation scenarios that demonstrate independence from the key causes of network dynamics: application setting and MANET configuration; including mobility or topology. Experimental results show that ROAM can constrain end-to-end delay, jitter and packet loss, to support real-time applications with critical timing requirements

An Introduction to Computer Networks

An open textbook for undergraduate and graduate courses on computer networks

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

Network delay control through adaptive queue management

Timeliness in delivering packets for delay-sensitive applications is an important QoS (Quality of Service) measure in many systems, notably those that need to provide real-time performance. In such systems, if delay-sensitive traffic is delivered to the destination beyond the deadline, then the packets will be rendered useless and dropped after received at the destination. Bandwidth that is already scarce and shared between network nodes is wasted in relaying these expired packets. This thesis proposes that a deterministic per-hop delay can be achieved by using a dynamic queue threshold concept to bound delay of each node. A deterministic per-hop delay is a key component in guaranteeing a deterministic end-to-end delay. The research aims to develop a generic approach that can constrain network delay of delay-sensitive traffic in a dynamic network. Two adaptive queue management schemes, namely, DTH (Dynamic THreshold) and ADTH (Adaptive DTH) are proposed to realize the claim. Both DTH and ADTH use the dynamic threshold concept to constrain queuing delay so that bounded average queuing delay can be achieved for the former and bounded maximum nodal delay can be achieved for the latter. DTH is an analytical approach, which uses queuing theory with superposition of N MMBP-2 (Markov Modulated Bernoulli Process) arrival processes to obtain a mapping relationship between average queuing delay and an appropriate queuing threshold, for queue management. While ADTH is an measurement-based algorithmic approach that can respond to the time-varying link quality and network dynamics in wireless ad hoc networks to constrain network delay. It manages a queue based on system performance measurements and feedback of error measured against a target delay requirement. Numerical analysis and Matlab simulation have been carried out for DTH for the purposes of validation and performance analysis. While ADTH has been evaluated in NS-2 simulation and implemented in a multi-hop wireless ad hoc network testbed for performance analysis. Results show that DTH and ADTH can constrain network delay based on the specified delay requirements, with higher packet loss as a trade-off

Evaluation of Deficit Round Robin Queue Discipline for Real-time Traffic Management in an RTP/RTCP Environment

Multimedia real-time traffic is deemed to be dominant in future communication systems. One of the reference applications to support real-time traffic is the Real-time Transport Protocol (RTP), which can be used to transmit multimedia contents on real-time basis. At the same time, Real-time Transmission Control Protocol (RTCP) is used for receiving feedback and getting information about the network. This paper proposes and evaluates a traffic management implementation in such an RTP/RTCP environment for congestion control. Deficit Round Robin queue discipline is used as the traffic management strategy instead of Random Early Detection and Drop Tail queue disciplines. A simulation campaign was performed to analyze the effects of implemented traffic strategies in RTP/RTCP environment and compare it with previous solutions. The obtained results highlight a significant difference in terms of jitter delay and packet losses and improvement the bandwidth utilization for real-time flows. Thus, we are able to provide quantitative evidence of the importance of the queue discipline to efficiently manage multimedia content

Annotierte interaktive nichtlineare Videos - Software Suite, Download- und Cache-Management

Modern Web technology makes the dream of fully interactive and enriched video come true. Nowadays it is possible to organize videos in a non-linear way playing in a sequence unknown in advance. Furthermore, additional information can be added to the video, ranging from short descriptions to animated images and further videos. This affords an easy and efficient to use authoring tool which is capable of the management of the single media objects, as well as a clear arrangement of the links between the parts. Tools of this kind can be found rarely and do mostly not provide the full range of needed functions. While providing an interactive experience to the viewer in the Web player, parallel plot sequences and additional information lead to an increased download volume. This may cause pauses during playback while elements have to be downloaded which are displayed with the video. A good quality of experience for these videos with small waiting times and a playback without interruptions is desired. This work presents the SIVA Suite to create the previously described annotated interactive non-linear videos. We propose a video model for interactivity, non-linearity, and annotations, which is implemented in an XML format, an authoring tool, and a player. Video is the main medium, whereby different scenes are linked to a scene graph. Time controlled additional content called annotations, like text, images, audio files, or videos, is added to the scenes. The user is able to navigate in the scene graph by selecting a button at a button panel. Furthermore, other navigational elements like a table of contents or a keyword search are provided. Besides the SIVA Suite, this thesis presents algorithms and strategies for download and cache management to provide a good quality of experience while watching the annotated interactive non-linear videos. Therefor, we implemented a standard-independent player framework. Integrated into a simulation environment, the framework allows to evaluate algorithms and strategies for the calculation of start-up times, and the selection of elements to pre-fetch into and delete from the cache. Their interaction during the playback of non-linear video contents can be analyzed. The algorithms and strategies can be used to minimize interruptions in the video flow after user interactions. Our extensive evaluation showed that our techniques result in faster start-up times and lesser interruptions in the video flow than those of other players. Knowledge of the structure of an interactive non-linear video can be used to minimize the start-up time at the beginning of a video while minimizing an increase in the overall download volume.Moderne Web-Technologien lassen den Traum von voll interaktiven und bereicherten Videos wahr werden. Heutzutage ist es möglich, Videos in nicht-linearer Art und Weise zu organisieren, welche dann in einer vorher unbekannten Reihenfolge abgespielt werden können. Weiterhin können den Videos Zusatzinformationen in Form von kurzen Beschreibungen über animierte Bilder bis hin zu weiteren Videos hinzugefügt werden. Dies erfordert ein einfach und effizient zu bedienendes Autorenwerkzeug, das in der Lage ist, sowohl einzelne Medien-Objekte zu verwalten, als auch die Verbindungen zwischen den einzelnen Teilen klar darzustellen. Tools dieser Art sind selten und bieten meist nicht den vollen benötigten Funktionsumfang. Während dem Betrachter dieses interaktive Erlebnis im Web Player zur Verfügung gestellt wird, führen parallele Handlungsstränge und zusätzliche Inhalte zu einem erhöhten Download-Volumen. Dies kann zu Pausen während der Wiedergabe führen, in denen Elemente vom Server geladen werden müssen, welche mit dem Video angezeigt werden sollen. Ein gutes Benutzungserlebnis für solche Videos kann durch geringe Wartezeiten und eine unterbrechungsfreie Wiedergabe erreicht werden. Diese Arbeit stellt die SIVA Suite vor, mit der die zuvor beschriebenen annotierten interaktiven nicht-linearen Videos erstellt werden können. Wir bilden Interaktivität, Nichtlinearität und Annotationen in einem Video-Model ab. Dieses wird in unserem XML-Format, Autorentool und Player umgesetzt. Als Leitmedium werden hierbei Videos verwendet, welche aufgeteilt in Szenen zu einer Graphstruktur zusammengefügt werden können. Zeitlich gesteuerte zusätzliche Inhalte, sogenannte Annotationen, wie Texte, Bilder, Audio-Dateien und Videos, werden den Szenen hinzugefügt. Der Betrachter kann im Szenengraph navigieren, indem er in einem bereitgestellten Button-Panel eine Nachfolgeszene auswählt. Andere Navigationselemente sind ein Inhaltsverzeichnis sowie eine Suchfunktion. Neben der SIVA Suite beschreibt diese Arbeit Algorithmen und Strategien für Download und Cache Management, um eine gute Nutzungserfahrung während der Betrachtung der annotierten interaktiven nicht-linearen Videos zu bieten. Ein Webstandard-unabhängiges Playerframework erlaubt es, das Zusammenspiel von Algorithmen und Strategien zu evaluieren, welche für die Berechnung der Start-Zeitpunkte für die Wiedergabe, sowie die Auswahl von vorauszuladenden sowie zu löschenden Elemente verwendet werden. Ziel ist es, Unterbrechungen zu minimieren, wenn der Ablauf des Videos durch Benutzerinteraktion beeinflusst wird. Unsere umfassende Evaluation zeigte, dass es möglich ist, kürzere Startup-Zeiten und weniger Unterbrechungen mit unseren Strategien zu erreichen, als bei der Verwendung der Strategien anderer Player. Die Kenntnis der Struktur des interaktiven nicht-linearen Videos kann dazu verwendet werden, die Startzeit am Anfang der Szenen zu minimieren, während das Download-Volumen nicht erhöht wird