6,000 research outputs found

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

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    QoE-Based Low-Delay Live Streaming Using Throughput Predictions

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    Recently, HTTP-based adaptive streaming has become the de facto standard for video streaming over the Internet. It allows clients to dynamically adapt media characteristics to network conditions in order to ensure a high quality of experience, that is, minimize playback interruptions, while maximizing video quality at a reasonable level of quality changes. In the case of live streaming, this task becomes particularly challenging due to the latency constraints. The challenge further increases if a client uses a wireless network, where the throughput is subject to considerable fluctuations. Consequently, live streams often exhibit latencies of up to 30 seconds. In the present work, we introduce an adaptation algorithm for HTTP-based live streaming called LOLYPOP (Low-Latency Prediction-Based Adaptation) that is designed to operate with a transport latency of few seconds. To reach this goal, LOLYPOP leverages TCP throughput predictions on multiple time scales, from 1 to 10 seconds, along with an estimate of the prediction error distribution. In addition to satisfying the latency constraint, the algorithm heuristically maximizes the quality of experience by maximizing the average video quality as a function of the number of skipped segments and quality transitions. In order to select an efficient prediction method, we studied the performance of several time series prediction methods in IEEE 802.11 wireless access networks. We evaluated LOLYPOP under a large set of experimental conditions limiting the transport latency to 3 seconds, against a state-of-the-art adaptation algorithm from the literature, called FESTIVE. We observed that the average video quality is by up to a factor of 3 higher than with FESTIVE. We also observed that LOLYPOP is able to reach a broader region in the quality of experience space, and thus it is better adjustable to the user profile or service provider requirements.Comment: Technical Report TKN-16-001, Telecommunication Networks Group, Technische Universitaet Berlin. This TR updated TR TKN-15-00

    Enabling error-resilient internet broadcasting using motion compensated spatial partitioning and packet FEC for the dirac video codec

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    Video transmission over the wireless or wired network require protection from channel errors since compressed video bitstreams are very sensitive to transmission errors because of the use of predictive coding and variable length coding. In this paper, a simple, low complexity and patent free error-resilient coding is proposed. It is based upon the idea of using spatial partitioning on the motion compensated residual frame without employing the transform coefficient coding. The proposed scheme is intended for open source Dirac video codec in order to enable the codec to be used for Internet broadcasting. By partitioning the wavelet transform coefficients of the motion compensated residual frame into groups and independently processing each group using arithmetic coding and Forward Error Correction (FEC), robustness to transmission errors over the packet erasure wired network could be achieved. Using the Rate Compatibles Punctured Code (RCPC) and Turbo Code (TC) as the FEC, the proposed technique provides gracefully decreasing perceptual quality over packet loss rates up to 30%. The PSNR performance is much better when compared with the conventional data partitioning only methods. Simulation results show that the use of multiple partitioning of wavelet coefficient in Dirac can achieve up to 8 dB PSNR gain over its existing un-partitioned method
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