88 research outputs found

    Design, performance analysis, and implementation of a super-scalar video-on-demand system

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    Video delivery technologies for large-scale deployment of multimedia applications

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    Support infrastructures for multimedia services with guaranteed continuity and QoS

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    Advances in wireless networking and content delivery systems are enabling new challenging provisioning scenarios where a growing number of users access multimedia services, e.g., audio/video streaming, while moving among different points of attachment to the Internet, possibly with different connectivity technologies, e.g., Wi-Fi, Bluetooth, and cellular 3G. That calls for novel middlewares capable of dynamically personalizing service provisioning to the characteristics of client environments, in particular to discontinuities in wireless resource availability due to handoffs. This dissertation proposes a novel middleware solution, called MUM, that performs effective and context-aware handoff management to transparently avoid service interruptions during both horizontal and vertical handoffs. To achieve the goal, MUM exploits the full visibility of wireless connections available in client localities and their handoff implementations (handoff awareness), of service quality requirements and handoff-related quality degradations (QoS awareness), and of network topology and resources available in current/future localities (location awareness). The design and implementation of the all main MUM components along with extensive on the field trials of the realized middleware architecture confirmed the validity of the proposed full context-aware handoff management approach. In particular, the reported experimental results demonstrate that MUM can effectively maintain service continuity for a wide range of different multimedia services by exploiting handoff prediction mechanisms, adaptive buffering and pre-fetching techniques, and proactive re-addressing/re-binding

    Design and performance analysis of a super-scalar video-on-demand system.

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    Lee Chung Hing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 61-63).Abstracts in English and Chinese.Acknowledgements --- p.iiAbstract --- p.iiiList of Figures --- p.viiChapter 1. --- Introduction --- p.1Chapter 1.1 --- Contributions of This Thesis --- p.3Chapter 1.2 --- Organizations of This Thesis --- p.3Chapter 1.3 --- Publication --- p.4Chapter 2. --- Overview of VoD Systems --- p.5Chapter 2.1 --- True VoD --- p.6Chapter 2.2 --- Near VoD --- p.7Chapter 2.3 --- Related Works --- p.9Chapter 2.3.1 --- Batching --- p.9Chapter 2.3.2 --- Patching --- p.11Chapter 2.3.3 --- Mcache --- p.11Chapter 2.3.4 --- Unified VoD --- p.12Chapter 2.4 --- Discussions --- p.15Chapter 3. --- Super-Scalar Architecture --- p.17Chapter 3.1 --- Transmission Scheduling --- p.20Chapter 3.2 --- Admission Control --- p.21Chapter 3.3 --- Channel Merging --- p.26Chapter 3.4 --- Interactive Control --- p.29Chapter 4. --- Performance Modeling --- p.31Chapter 4.1 --- Waiting Time for Statically-Admitted Clients --- p.32Chapter 4.2 --- Waiting Time for Dynamically-Admitted Clients --- p.33Chapter 4.3 --- Admission Threshold --- p.38Chapter 4.4 --- Channel Partitioning --- p.39Chapter 5. --- Performance Evaluation --- p.40Chapter 5.1 --- Model Validation --- p.40Chapter 5.2 --- Channel Partitioning --- p.42Chapter 5.3 --- Latency Comparisons --- p.44Chapter 5.4 --- Channel Requirement --- p.46Chapter 5.5 --- Performance at Light Loads --- p.47Chapter 5.6 --- Multiplexing Gain --- p.49Chapter 6. --- Implementation and Benchmarking --- p.51Chapter 6.1 --- Implementation Description --- p.51Chapter 6.2 --- Benchmarking --- p.53Chapter 6.2.1 --- Benchmarking Setup --- p.53Chapter 6.2.2 --- Benchmarking Result --- p.55Chapter 7. --- Conclusion --- p.56Appendix --- p.57Bibliography --- p.6

    Peer-to-peer stream merging for stored multimedia

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    In recent years, with the fast development of resource capability of both the Internet and personal computers, multimedia applications like video-on-demand (VOD) streaming have gained dramatic growth and been shown to be potential killer applications in the current and next-generation Internet. Scalable deployment of these applications has become a hot problem area due to the potentially high server and network bandwidth required in these systems.The conventional approach in a VOD streaming system dedicates a media stream for each client request, which is not scalable in a wide-area delivery system serving potentially very large numbers of clients. Recently, various efficient delivery techniques have been proposed to improve the scalability of VOD delivery systems. One approach is to use a scalable delivery protocol based on multicast, such as periodic broadcast or stream merging. These protocols have been mostly developed for single-server based systems and attempt to have each media stream serve as many clients as possible, so as to minimize the required server and network bandwidth. However, the performance improvements possible with techniques that deliver all streams from a single server are limited, especially regarding the required network bandwidth. Another approach is based on proxy caching and content replication, such as in content delivery networks (CDN). Although this approach is able to effectively distribute load across multiple CDN servers, the cost of this approach may be high.With the focus on further improving the system efficiency regarding the server and network bandwidth requirement, a new scalable streaming protocol is developed in this work. It adapts a previously proposed technique called hierarchical multicast stream merging (HMSM) to use a peer-to-peer delivery approach. To be more efficient in media delivery, the conventional early merging policy associated with HMSM is extended to be compatible with the peer-to-peer environment, and various peer selection policies are designed for initiation of media streams. The impact of limited peer resource capability is also studied in this work. In the performance study, a number of simulation experiments are conducted to evaluate the performance of the new protocol and various design policies, and promising results are reported

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

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    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

    Proactive Mechanisms for Video-on-Demand Content Delivery

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    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
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