Network coding for transport protocols

With the proliferation of smart devices that require Internet connectivity anytime, anywhere, and the recent technological advances that make it possible, current networked systems will have to provide a various range of services, such as content distribution, in a wide range of settings, including wireless environments. Wireless links may experience temporary losses, however, TCP, the de facto protocol for robust unicast communications, reacts by reducing the congestion window drastically and injecting less traffic in the network. Consequently the wireless links are underutilized and the overall performance of the TCP protocol in wireless environments is poor. As content delivery (i.e. multicasting) services, such as BBC iPlayer, become popular, the network needs to support the reliable transport of the data at high rates, and with specific delay constraints. A typical approach to deliver content in a scalable way is to rely on peer-to-peer technology (used by BitTorrent, Spotify and PPLive), where users share their resources, including bandwidth, storage space, and processing power. Still, these systems suffer from the lack of incentives for resource sharing and cooperation, and this problem is exacerbated in the presence of heterogenous users, where a tit-for-tat scheme is difficult to implement. Due to the issues highlighted above, current network architectures need to be changed in order to accommodate the users¿ demands for reliable and quality communications. In other words, the emergent need for advanced modes of information transport requires revisiting and improving network components at various levels of the network stack. The innovative paradigm of network coding has been shown as a promising technique to change the design of networked systems, by providing a shift from how data flows traditionally move through the network. This shift implies that data flows are no longer kept separate, according to the ¿store-and-forward¿ model, but they are also processed and mixed in the network. By appropriately combining data by means of network coding, it is expected to obtain significant benefits in several areas of network design and architecture. In this thesis, we set out to show the benefits of including network coding into three communication paradigms, namely point-topoint communications (e.g. unicast), point-to-multipoint communications (e.g. multicast), and multipoint-to-multipoint communications (e.g. peer-to-peer networks). For the first direction, we propose a network coding-based multipath scheme and show that TCP unicast sessions are feasible in highly volatile wireless environments. For point-to-multipoint communications, we give an algorithm to optimally achieve all the rate pairs from the rate region in the case of degraded multicast over the combination network. We also propose a system for live streaming that ensures reliability and quality of service to heterogenous users, even if data transmissions occur over lossy wireless links. Finally, for multipoint-to-multipoint communications, we design a system to provide incentives for live streaming in a peer-to-peer setting, where users have subscribed to different levels of quality. Our work shows that network coding enables a reliable transport of data, even in highly volatile environments, or in delay sensitive scenarios such as live streaming, and facilitates the implementation of an efficient incentive system, even in the presence of heterogenous users. Thus, network coding can solve the challenges faced by next generation networks in order to support advanced information transport.Postprint (published version

Provider-Controlled Bandwidth Management for HTTP-based Video Delivery

Over the past few years, a revolution in video delivery technology has taken place as mobile viewers and over-the-top (OTT) distribution paradigms have significantly changed the landscape of video delivery services. For decades, high quality video was only available in the home via linear television or physical media. Though Web-based services brought video to desktop and laptop computers, the dominance of proprietary delivery protocols and codecs inhibited research efforts. The recent emergence of HTTP adaptive streaming protocols has prompted a re-evaluation of legacy video delivery paradigms and introduced new questions as to the scalability and manageability of OTT video delivery. This dissertation addresses the question of how to enable for content and network service providers the ability to monitor and manage large numbers of HTTP adaptive streaming clients in an OTT environment. Our early work focused on demonstrating the viability of server-side pacing schemes to produce an HTTP-based streaming server. We also investigated the ability of client-side pacing schemes to work with both commodity HTTP servers and our HTTP streaming server. Continuing our client-side pacing research, we developed our own client-side data proxy architecture which was implemented on a variety of mobile devices and operating systems. We used the portable client architecture as a platform for investigating different rate adaptation schemes and algorithms. We then concentrated on evaluating the network impact of multiple adaptive bitrate clients competing for limited network resources, and developing schemes for enforcing fair access to network resources. The main contribution of this dissertation is the definition of segment-level client and network techniques for enforcing class of service (CoS) differentiation between OTT HTTP adaptive streaming clients. We developed a segment-level network proxy architecture which works transparently with adaptive bitrate clients through the use of segment replacement. We also defined a segment-level rate adaptation algorithm which uses download aborts to enforce CoS differentiation across distributed independent clients. The segment-level abstraction more accurately models application-network interactions and highlights the difference between segment-level and packet-level time scales. Our segment-level CoS enforcement techniques provide a foundation for creating scalable managed OTT video delivery services

Codage réseau pour des applications multimédias avancées

Network coding is a paradigm that allows an efficient use of the capacity of communication networks. It maximizes the throughput in a multi-hop multicast communication and reduces the delay. In this thesis, we focus our attention to the integration of the network coding framework to multimedia applications, and in particular to advanced systems that provide enhanced video services to the users. Our contributions concern several instances of advanced multimedia communications: an efficient framework for transmission of a live stream making joint use of network coding and multiple description coding; a novel transmission strategy for lossy wireless networks that guarantees a trade-off between loss resilience and short delay based on a rate-distortion optimized scheduling of the video frames, that we also extended to the case of interactive multi-view streaming; a distributed social caching system that, using network coding in conjunction with the knowledge of the users' preferences in terms of views, is able to select a replication scheme such that to provide a high video quality by accessing only other members of the social group without incurring the access cost associated with a connection to a central server and without exchanging large tables of metadata to keep track of the replicated parts; and, finally, a study on using blind source separation techniques to reduce the overhead incurred by network coding schemes based on error-detecting techniques such as parity coding and message digest generation. All our contributions are aimed at using network coding to enhance the quality of video transmission in terms of distortion and delay perceivedLe codage réseau est un paradigme qui permet une utilisation efficace du réseau. Il maximise le débit dans un réseau multi-saut en multicast et réduit le retard. Dans cette thèse, nous concentrons notre attention sur l’intégration du codage réseau aux applications multimédias, et en particulier aux systèmes avancès qui fournissent un service vidéo amélioré pour les utilisateurs. Nos contributions concernent plusieurs scénarios : un cadre de fonctions efficace pour la transmission de flux en directe qui utilise à la fois le codage réseau et le codage par description multiple, une nouvelle stratégie de transmission pour les réseaux sans fil avec perte qui garantit un compromis entre la résilience vis-à-vis des perte et la reduction du retard sur la base d’une optimisation débit-distorsion de l'ordonnancement des images vidéo, que nous avons également étendu au cas du streaming multi-vue interactive, un système replication sociale distribuée qui, en utilisant le réseau codage en relation et la connaissance des préférences des utilisateurs en termes de vue, est en mesure de sélectionner un schéma de réplication capable de fournir une vidéo de haute qualité en accédant seulement aux autres membres du groupe social, sans encourir le coût d’accès associé à une connexion à un serveur central et sans échanger des larges tables de métadonnées pour tenir trace des éléments répliqués, et, finalement, une étude sur l’utilisation de techniques de séparation aveugle de source -pour réduire l’overhead encouru par les schémas de codage réseau- basé sur des techniques de détection d’erreur telles que le codage de parité et la génération de message digest

Partitioning and Offloading for IoT and Video Streaming Applications that Utilize Computing Resources at the Network Edge

The Internet of Things (IoT) is a concept in which physical objects embedded with sensors, actuators, and network connectivity can communicate and react to their surroundings. IoT applications connect physical objects for the purpose of decision making by sensing and analysing generated data from the embedded sensors in physical objects. IoT applications are growing rapidly as sensors become less expensive. Sensors generate large amounts of data that may meaningless unless the data is used to derive knowledge with in a certain period of time. Stream processing paradigm is used by IoT to provide requirements of IoT applications. In a stream processing paradigm, unlike traditional data bases, data is not stored but rather processed as it is generated. To transfer generated data from distributed data sources to a processing center such as cloud may not allow for real-time processing due to the network delay. Another high-demand application is live streaming of video. The performance of live video stream systems is inferior when there is a sudden large demand in the number of users. This thesis addresses some of the limitations of current architectures for video streaming systems and IoT applications based on the use of nearby computing resources (e.g., cloudlet, fog). First, we addressed the degrading performance in video stream systems when a flash crowd occurs. The performance of video streaming systems is affected by flash crowd and degrade the quality of service for subscribers to the content delivery system. A flash crowd happens when there is a sudden large increase in the number of users. Therefore, flash crowds increase network traffic for any particular server. The main challenge is to make sure that the video streaming system has sufficient capacity to handle the occurrence of flash crowds. Second, we address the limitation of current architectures for running mobile applications by introducing a dynamic partitioning and offloading of a mobile application. Mobile devices have limited resources including short battery life, storage capacity and processor performance. This limits the applications that can run on it. Mobile applications can be partitioned so that some of the application runs on a cloud. This works well for applications with relatively little data to be transferred and that do not have a high level of interaction with the user. Challenges with applications that have large amounts of data to be transferred and have a high level interactiveness is the high latency incurred by the network and packet loss of the wireless network. A mobile application can be partitioned so that part of it runs on a nearby computing resource e.g., fog node or cloudlet. This thesis presents a framework that introduces fine-grained offloading approach and support for runtime and dynamic partitioning of an application. Third, we present a solution for placement of stream operators over distributed fog nodes for live processing of data streams from geographically distributed data sources. This placement of stream operators takes place in such a way that it supports applications with a high volume of data that require real-time (or near real-time) analysis To this end, this thesis proposed a set of algorithms for placement of stream operators among fog nodes

Real-time video streaming using peer-to-peer for video distribution

The growth of the Internet has led to research and development of several new and useful applications including video streaming. Commercial experiments are underway to determine the feasibility of multimedia broadcasting using packet based data networks alongside traditional over-the-air broadcasting. Broadcasting companies are offering low cost or free versions of video content online to both guage and at the same time generate popularity. In addition to television broadcasting, video streaming is used in a number of application areas including video conferencing, telecommuting and long distance education. Large scale video streaming has not become as widespread or widely deployed as could be expected. The reason for this is the high bandwidth requirement (and thus high cost) associated with video data. Provision of a constant stream of video data on a medium to large scale typically consumes a significant amount of bandwidth. An effect of this is that encoding bit rates are lowered and consequently video quality is degraded resulting in even slower uptake rates for video streaming services. The aim of this dissertation is to investigate peer-to-peer streaming as a potential solution to this bandwidth problem. The proposed peer-to-peer based solution relies on end user co-operation for video data distribution. This approach is highly effective in reducing the outgoing bandwidth requirement for the video streaming server. End users redistribute received video chunks amongst their respective peers and in so doing increase the potential capacity of the entire network for supporting more clients. A secondary effect of such a system is that encoding capabilities (including higher encoding bit rates or encoding of additional sub-channels) can be enhanced. Peer-to-peer distribution enables any regular user to stream video to large streaming networks with many viewers. This research includes a detailed overview of the fields of video streaming and peer-to-peer networking. Techniques for optimal video preparation and data distribution were investigated. A variety of academic and commercial peer-to-peer based multimedia broadcasting systems were analysed as a means to further define and place the proposed implementation in context with respect to other peercasting implementations. A proof-of-concept of the proposed implementation was developed, mathematically analyzed and simulated in a typical deployment scenario. Analysis was carried out to predict simulation performance and as a form of design evaluation and verification. The analysis highlighted some critical areas which resulted in adaptations to the initial design as well as conditions under which performance can be guaranteed. A simulation of the proof-of-concept system was used to determine the extent of bandwidth savings for the video server. The aim of the simulations was to show that it is possible to encode and deliver video data in real time over a peer-to-peer network. The proposed system achieved expectations and showed significant bandwidth savings for a sustantially large video streaming audience. The implementation was able to encode video in real time and continually stream video packets on time to connected peers while continually supporting network growth by connecting additional peers (or stream viewers). The system performed well and showed good performance under typical real world restrictions on available bandwith capacity.Dissertation (MEng)--University of Pretoria, 2009.Electrical, Electronic and Computer Engineeringunrestricte

Actas da 10ª Conferência sobre Redes de Computadores

Universidade do MinhoCCTCCentro AlgoritmiCisco SystemsIEEE Portugal Sectio

Profiling Large-scale Live Video Streaming and Distributed Applications

PhDToday, distributed applications run at data centre and Internet scales, from intensive data analysis, such as MapReduce; to the dynamic demands of a worldwide audience, such as YouTube. The network is essential to these applications at both scales. To provide adequate support, we must understand the full requirements of the applications, which are revealed by the workloads. In this thesis, we study distributed system applications at different scales to enrich this understanding. Large-scale Internet applications have been studied for years, such as social networking service (SNS), video on demand (VoD), and content delivery networks (CDN). An emerging type of video broadcasting on the Internet featuring crowdsourced live video streaming has garnered attention allowing platforms such as Twitch to attract over 1 million concurrent users globally. To better understand Twitch, we collected real-time popularity data combined with metadata about the contents and found the broadcasters rather than the content drives its popularity. Unlike YouTube and Netflix where content can be cached, video streaming on Twitch is generated instantly and needs to be delivered to users immediately to enable real-time interaction. Thus, we performed a large-scale measurement of Twitchs content location revealing the global footprint of its infrastructure as well as discovering the dynamic stream hosting and client redirection strategies that helped Twitch serve millions of users at scale. We next consider applications that run inside the data centre. Distributed computing applications heavily rely on the network due to data transmission needs and the scheduling of resources and tasks. One successful application, called Hadoop, has been widely deployed for Big Data processing. However, little work has been devoted to understanding its network. We found the Hadoop behaviour is limited by hardware resources and processing jobs presented. Thus, after characterising the Hadoop traffic on our testbed with a set of benchmark jobs, we built a simulator to reproduce Hadoops job traffic With the simulator, users can investigate the connections between Hadoop traffic and network performance without additional hardware cost. Different network components can be added to investigate the performance, such as network topologies, queue policies, and transport layer protocols. In this thesis, we extended the knowledge of networking by investigated two widelyused applications in the data centre and at Internet scale. We (i)studied the most popular live video streaming platform Twitch as a new type of Internet-scale distributed application revealing that broadcaster factors drive the popularity of such platform, and we (ii)discovered the footprint of Twitch streaming infrastructure and the dynamic stream hosting and client redirection strategies to provide an in-depth example of video streaming delivery occurring at the Internet scale, also we (iii)investigated the traffic generated by a distributed application by characterising the traffic of Hadoop under various parameters, (iv)with such knowledge, we built a simulation tool so users can efficiently investigate the performance of different network components under distributed applicationQueen Mary University of Londo

Content-Aware Multimedia Communications

The demands for fast, economic and reliable dissemination of multimedia information are steadily growing within our society. While people and economy increasingly rely on communication technologies, engineers still struggle with their growing complexity. Complexity in multimedia communication originates from several sources. The most prominent is the unreliability of packet networks like the Internet. Recent advances in scheduling and error control mechanisms for streaming protocols have shown that the quality and robustness of multimedia delivery can be improved significantly when protocols are aware of the content they deliver. However, the proposed mechanisms require close cooperation between transport systems and application layers which increases the overall system complexity. Current approaches also require expensive metrics and focus on special encoding formats only. A general and efficient model is missing so far. This thesis presents efficient and format-independent solutions to support cross-layer coordination in system architectures. In particular, the first contribution of this work is a generic dependency model that enables transport layers to access content-specific properties of media streams, such as dependencies between data units and their importance. The second contribution is the design of a programming model for streaming communication and its implementation as a middleware architecture. The programming model hides the complexity of protocol stacks behind simple programming abstractions, but exposes cross-layer control and monitoring options to application programmers. For example, our interfaces allow programmers to choose appropriate failure semantics at design time while they can refine error protection and visibility of low-level errors at run-time. Based on some examples we show how our middleware simplifies the integration of stream-based communication into large-scale application architectures. An important result of this work is that despite cross-layer cooperation, neither application nor transport protocol designers experience an increase in complexity. Application programmers can even reuse existing streaming protocols which effectively increases system robustness.Der Bedarf unsere Gesellschaft nach kostengünstiger und zuverlässiger Kommunikation wächst stetig. Während wir uns selbst immer mehr von modernen Kommunikationstechnologien abhängig machen, müssen die Ingenieure dieser Technologien sowohl den Bedarf nach schneller Einführung neuer Produkte befriedigen als auch die wachsende Komplexität der Systeme beherrschen. Gerade die Übertragung multimedialer Inhalte wie Video und Audiodaten ist nicht trivial. Einer der prominentesten Gründe dafür ist die Unzuverlässigkeit heutiger Netzwerke, wie z.B.~dem Internet. Paketverluste und schwankende Laufzeiten können die Darstellungsqualität massiv beeinträchtigen. Wie jüngste Entwicklungen im Bereich der Streaming-Protokolle zeigen, sind jedoch Qualität und Robustheit der Übertragung effizient kontrollierbar, wenn Streamingprotokolle Informationen über den Inhalt der transportierten Daten ausnutzen. Existierende Ansätze, die den Inhalt von Multimediadatenströmen beschreiben, sind allerdings meist auf einzelne Kompressionsverfahren spezialisiert und verwenden berechnungsintensive Metriken. Das reduziert ihren praktischen Nutzen deutlich. Außerdem erfordert der Informationsaustausch eine enge Kooperation zwischen Applikationen und Transportschichten. Da allerdings die Schnittstellen aktueller Systemarchitekturen nicht darauf vorbereitet sind, müssen entweder die Schnittstellen erweitert oder alternative Architekturkonzepte geschaffen werden. Die Gefahr beider Varianten ist jedoch, dass sich die Komplexität eines Systems dadurch weiter erhöhen kann. Das zentrale Ziel dieser Dissertation ist es deshalb, schichtenübergreifende Koordination bei gleichzeitiger Reduzierung der Komplexität zu erreichen. Hier leistet die Arbeit zwei Beträge zum aktuellen Stand der Forschung. Erstens definiert sie ein universelles Modell zur Beschreibung von Inhaltsattributen, wie Wichtigkeiten und Abhängigkeitsbeziehungen innerhalb eines Datenstroms. Transportschichten können dieses Wissen zur effizienten Fehlerkontrolle verwenden. Zweitens beschreibt die Arbeit das Noja Programmiermodell für multimediale Middleware. Noja definiert Abstraktionen zur Übertragung und Kontrolle multimedialer Ströme, die die Koordination von Streamingprotokollen mit Applikationen ermöglichen. Zum Beispiel können Programmierer geeignete Fehlersemantiken und Kommunikationstopologien auswählen und den konkreten Fehlerschutz dann zur Laufzeit verfeinern und kontrolliere