Video-on-Demand over Internet: a survey of existing systems and solutions

Video-on-Demand is a service where movies are delivered to distributed users with low delay and free interactivity. The traditional client/server architecture experiences scalability issues to provide video streaming services, so there have been many proposals of systems, mostly based on a peer-to-peer or on a hybrid server/peer-to-peer solution, to solve this issue. This work presents a survey of the currently existing or proposed systems and solutions, based upon a subset of representative systems, and defines selection criteria allowing to classify these systems. These criteria are based on common questions such as, for example, is it video-on-demand or live streaming, is the architecture based on content delivery network, peer-to-peer or both, is the delivery overlay tree-based or mesh-based, is the system push-based or pull-based, single-stream or multi-streams, does it use data coding, and how do the clients choose their peers. Representative systems are briefly described to give a summarized overview of the proposed solutions, and four ones are analyzed in details. Finally, it is attempted to evaluate the most promising solutions for future experiments. Résumé La vidéo à la demande est un service où des films sont fournis à distance aux utilisateurs avec u

Dynamic Scaling of VoD Services into Hybrid Clouds with Cost Minimization and QoS Guarantee

A large-scale video-on-demand (VoD) service demands huge server costs, to provision thousands of videos to millions of users with high streaming quality. As compared to the traditional practice of relying on large on-premise server clusters, the emerging platforms of geo-distributed public clouds promise a more economic solution: their on-demand resource provisioning can constitute ideal supplements of resources from on-premise servers, and effectively support dynamic scaling of the VoD service at different times. Promising though it is, significant technical challenges persist before it turns into reality: how shall the service provider dynamically replicate videos and dispatch user requests over the hybrid platform, such that the service quality and the minimization of overall cost can be guaranteed over the long run of the system? In this paper, we present a dynamic algorithm that optimally makes decisions on video replication and user request dispatching in a hybrid cloud of on-premise servers and geo-distributed cloud data centers, based on the Lyapunov optimization framework. We rigorously prove that this algorithm can nicely bound the streaming delays within the preset QoS target in cases of arbitrary request arrival patterns, and guarantee that the overall cost is within a small constant gap from the optimum achieved by a T-slot lookahead mechanism with known information into the future. We evaluate our algorithm with extensive simulations under realistic settings, and demonstrate that cost minimization and smooth playback can be achieved in cases of volatile user demands.published_or_final_versio

Service oriented networking for multimedia applications in broadband wireless networks

Extensive efforts have been focused on deploying broadband wireless networks. Providing mobile users with high speed network connectivity will let them run various multimedia applications on their wireless devices. In order to successfully deploy and operate broadband wireless networks, it is crucial to design efficient methods for supporting various services and applications in broadband wireless networks. Moreover, the existing access-oriented networking solutions are not able to fully address all the issues of supporting various applications with different quality of service requirements. Thus, service-oriented networking has been recently proposed and has gained much attention. This dissertation discusses the challenges and possible solutions for supporting multimedia applications in broadband wireless networks. The service requirements of different multimedia applications such as video streaming and Voice over IP (VoIP) are studied and some novel service-oriented networking solutions for supporting these applications in broadband wireless networks are proposed. The performance of these solutions is examined in WiMAX networks which are the promising technology for broadband wireless access in the near future. WiMAX networks are based on the IEEE 802.16 standards which have defined different Quality of Service (QoS) classes to support a broad range of applications with varying service requirements to mobile and stationary users. The growth of multimedia traffic that requires special quality of service from the network will impose new constraints on network designers who should wisely allocate the limited resources to users based on their required quality of service. An efficient resource management and network design depends upon gaining accurate information about the traffic profile of user applications. In this dissertation, the access level traffic profile of VoIP applications are studied first, and then a realistic distribution model for VoIP traffic is proposed. Based on this model, an algorithm to allocate resources for VoIP applications in WiMAX networks is investigated. Later, the challenges and possible solutions for transmitting MPEG video streams in wireless networks are discussed. The MPEG traffic model adopted by the WiMAX Forum is introduced and different application-oriented solutions for enhancing the performance of wireless networks with respect to MPEG video streaming applications are explained. An analytical framework to verify the performance of the proposed solutions is discoursed, and it is shown that the proposed solutions will improve the efficiency of VoIP applications and the quality of streaming applications over wireless networks. Finally, conclusions are drawn and future works are discussed

Entrega de conteúdos multimédia em over-the-top: caso de estudo das gravações automáticas

Doutoramento em Engenharia EletrotécnicaOver-The-Top (OTT) multimedia delivery is a very appealing approach for providing ubiquitous, exible, and globally accessible services capable of low-cost and unrestrained device targeting. In spite of its appeal, the underlying delivery architecture must be carefully planned and optimized to maintain a high Qualityof- Experience (QoE) and rational resource usage, especially when migrating from services running on managed networks with established quality guarantees. To address the lack of holistic research works on OTT multimedia delivery systems, this Thesis focuses on an end-to-end optimization challenge, considering a migration use-case of a popular Catch-up TV service from managed IP Television (IPTV) networks to OTT. A global study is conducted on the importance of Catch-up TV and its impact in today's society, demonstrating the growing popularity of this time-shift service, its relevance in the multimedia landscape, and tness as an OTT migration use-case. Catch-up TV consumption logs are obtained from a Pay-TV operator's live production IPTV service containing over 1 million subscribers to characterize demand and extract insights from service utilization at a scale and scope not yet addressed in the literature. This characterization is used to build demand forecasting models relying on machine learning techniques to enable static and dynamic optimization of OTT multimedia delivery solutions, which are able to produce accurate bandwidth and storage requirements' forecasts, and may be used to achieve considerable power and cost savings whilst maintaining a high QoE. A novel caching algorithm, Most Popularly Used (MPU), is proposed, implemented, and shown to outperform established caching algorithms in both simulation and experimental scenarios. The need for accurate QoE measurements in OTT scenarios supporting HTTP Adaptive Streaming (HAS) motivates the creation of a new QoE model capable of taking into account the impact of key HAS aspects. By addressing the complete content delivery pipeline in the envisioned content-aware OTT Content Delivery Network (CDN), this Thesis demonstrates that signi cant improvements are possible in next-generation multimedia delivery solutions.A entrega de conteúdos multimédia em Over-The-Top (OTT) e uma proposta atractiva para fornecer um serviço flexível e globalmente acessível, capaz de alcançar qualquer dispositivo, com uma promessa de baixos custos. Apesar das suas vantagens, e necessario um planeamento arquitectural detalhado e optimizado para manter níveis elevados de Qualidade de Experiência (QoE), em particular aquando da migração dos serviços suportados em redes geridas com garantias de qualidade pré-estabelecidas. Para colmatar a falta de trabalhos de investigação na área de sistemas de entrega de conteúdos multimédia em OTT, esta Tese foca-se na optimização destas soluções como um todo, partindo do caso de uso de migração de um serviço popular de Gravações Automáticas suportado em redes de Televisão sobre IP (IPTV) geridas, para um cenário de entrega em OTT. Um estudo global para aferir a importância das Gravações Automáticas revela a sua relevância no panorama de serviços multimédia e a sua adequação enquanto caso de uso de migração para cenários OTT. São obtidos registos de consumos de um serviço de produção de Gravações Automáticas, representando mais de 1 milhão de assinantes, para caracterizar e extrair informação de consumos numa escala e âmbito não contemplados ate a data na literatura. Esta caracterização e utilizada para construir modelos de previsão de carga, tirando partido de sistemas de machine learning, que permitem optimizações estáticas e dinâmicas dos sistemas de entrega de conteúdos em OTT através de previsões das necessidades de largura de banda e armazenamento, potenciando ganhos significativos em consumo energético e custos. Um novo mecanismo de caching, Most Popularly Used (MPU), demonstra um desempenho superior as soluções de referencia, quer em cenários de simulação quer experimentais. A necessidade de medição exacta da QoE em streaming adaptativo HTTP motiva a criaçao de um modelo capaz de endereçar aspectos específicos destas tecnologias adaptativas. Ao endereçar a cadeia completa de entrega através de uma arquitectura consciente dos seus conteúdos, esta Tese demonstra que são possíveis melhorias de desempenho muito significativas nas redes de entregas de conteúdos em OTT de próxima geração

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

Evaluation of unidirectional background push content download services for the delivery of television programs

Este trabajo de tesis presenta los servicios de descarga de contenido en modo push como un mecanismo eficiente para el envío de contenido de televisión pre-producido sobre redes de difusión. Hoy en día, los operadores de red dedican una cantidad considerable de recursos de red a la entrega en vivo de contenido televisivo, tanto sobre redes de difusión como sobre conexiones unidireccionales. Esta oferta de servicios responde únicamente a requisitos comerciales: disponer de los contenidos televisivos en cualquier momento y lugar. Sin embargo, desde un punto de vista estrictamente académico, el envío en vivo es únicamente un requerimiento para el contenido en vivo, no para contenidos que ya han sido producidos con anterioridad a su emisión. Más aún, la difusión es solo eficiente cuando el contenido es suficientemente popular. Los servicios bajo estudio en esta tesis utilizan capacidad residual en redes de difusión para enviar contenido pre-producido para que se almacene en los equipos de usuario. La propuesta se justifica únicamente por su eficiencia. Por un lado, genera valor de recursos de red que no se aprovecharían de otra manera. Por otro lado, realiza la entrega de contenidos pre-producidos y populares de la manera más eficiente: sobre servicios de descarga de contenidos en difusión. Los resultados incluyen modelos para la popularidad y la duración de contenidos, valiosos para cualquier trabajo de investigación basados en la entrega de contenidos televisivos. Además, la tesis evalúa la capacidad residual disponible en redes de difusión, por medio de estudios empíricos. Después, estos resultados son utilizados en simulaciones que evalúan las prestaciones de los servicios propuestos en escenarios diferentes y para aplicaciones diferentes. La evaluación demuestra que este tipo de servicios son un recurso muy útil para la entrega de contenido televisivo.This thesis dissertation presents background push Content Download Services as an efficient mechanism to deliver pre-produced television content through existing broadcast networks. Nowadays, network operators dedicate a considerable amount of network resources to live streaming live, through both broadcast and unicast connections. This service offering responds solely to commercial requirements: Content must be available anytime and anywhere. However, from a strictly academic point of view, live streaming is only a requirement for live content and not for pre-produced content. Moreover, broadcasting is only efficient when the content is sufficiently popular. The services under study in this thesis use residual capacity in broadcast networks to push popular, pre-produced content to storage capacity in customer premises equipment. The proposal responds only to efficiency requirements. On one hand, it creates value from network resources otherwise unused. On the other hand, it delivers popular pre-produced content in the most efficient way: through broadcast download services. The results include models for the popularity and the duration of television content, valuable for any research work dealing with file-based delivery of television content. Later, the thesis evaluates the residual capacity available in broadcast networks through empirical studies. These results are used in simulations to evaluate the performance of background push content download services in different scenarios and for different applications. The evaluation proves that this kind of services can become a great asset for the delivery of television contentFraile Gil, F. (2013). Evaluation of unidirectional background push content download services for the delivery of television programs [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/31656TESI