6,282 research outputs found

    An autonomic delivery framework for HTTP adaptive streaming in multicast-enabled multimedia access networks

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    The consumption of multimedia services over HTTP-based delivery mechanisms has recently gained popularity due to their increased flexibility and reliability. Traditional broadcast TV channels are now offered over the Internet, in order to support Live TV for a broad range of consumer devices. Moreover, service providers can greatly benefit from offering external live content (e. g., YouTube, Hulu) in a managed way. Recently, HTTP Adaptive Streaming (HAS) techniques have been proposed in which video clients dynamically adapt their requested video quality level based on the current network and device state. Unlike linear TV, traditional HTTP- and HAS-based video streaming services depend on unicast sessions, leading to a network traffic load proportional to the number of multimedia consumers. In this paper we propose a novel HAS-based video delivery architecture, which features intelligent multicasting and caching in order to decrease the required bandwidth considerably in a Live TV scenario. Furthermore we discuss the autonomic selection of multicasted content to support Video on Demand (VoD) sessions. Experiments were conducted on a large scale and realistic emulation environment and compared with a traditional HAS-based media delivery setup using only unicast connections

    Adaptive Multicast of Multi-Layered Video: Rate-Based and Credit-Based Approaches

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    Network architectures that can efficiently transport high quality, multicast video are rapidly becoming a basic requirement of emerging multimedia applications. The main problem complicating multicast video transport is variation in network bandwidth constraints. An attractive solution to this problem is to use an adaptive, multi-layered video encoding mechanism. In this paper, we consider two such mechanisms for the support of video multicast; one is a rate-based mechanism that relies on explicit rate congestion feedback from the network, and the other is a credit-based mechanism that relies on hop-by-hop congestion feedback. The responsiveness, bandwidth utilization, scalability and fairness of the two mechanisms are evaluated through simulations. Results suggest that while the two mechanisms exhibit performance trade-offs, both are capable of providing a high quality video service in the presence of varying bandwidth constraints.Comment: 11 page

    Experimental Evaluation of Large Scale WiFi Multicast Rate Control

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    WiFi multicast to very large groups has gained attention as a solution for multimedia delivery in crowded areas. Yet, most recently proposed schemes do not provide performance guarantees and none have been tested at scale. To address the issue of providing high multicast throughput with performance guarantees, we present the design and experimental evaluation of the Multicast Dynamic Rate Adaptation (MuDRA) algorithm. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. MuDRA relies on feedback from some nodes collected via a light-weight protocol and dynamically adjusts the rate adaptation response time. Our experimental evaluation of MuDRA on the ORBIT testbed with over 150 nodes shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of receivers while meeting quality requirements. MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality

    Random Linear Network Coding for 5G Mobile Video Delivery

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    An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC). In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.Comment: Invited paper for Special Issue "Network and Rateless Coding for Video Streaming" - MDPI Informatio

    Multicast Mobility in Mobile IP Version 6 (MIPv6) : Problem Statement and Brief Survey

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    Overlay networks for smart grids

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