This document summarizes a research paper on providing differentiated quality video multicast in multirate wireless networks. It proposes a rate scheduling model that selects the optimal transmission bitrate for each video frame to maximize total visual quality while guaranteeing a minimum quality. It also presents a practical protocol called QDM that constructs cluster-based groups, adapts transmission rates based on quality perceived by cluster heads, and is suitable for real-time streaming. Simulation results show QDM can efficiently adapt to network dynamics and variable video bitrates, producing a 2-5 dB gain in average video quality over leader-based approaches.
A Real-Time Adaptive Algorithm for Video Streaming over Multiple Wireless Acc...Priti Kana
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A Real-Time Adaptive Algorithm for Video Streaming over Multiple Wireless Acc...Priti Kana
JP INFOTECH, offering bulk 2014 and 2015 IEEE Project titles for CSE, IT, ECE, EEE final year students. We are guide to give a best projects for your academic and future career.
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Providing network connectivity and services, such as data, voice, live TV, high- definition (HD) on-demand video, and mobile services, EMC caters to customers with operations in some of the most remote corners of the planet. Managing satellite bandwidth requires sophisticated monitoring tools to ensure consistent performance of voice, video and data during events, such as rain, that can affect the quality. This telecommunications leader prides itself on delivering carrier-class services through its global mobility platform, using its hybrid satellite and terrestrial broadband network.
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Revamping quality of service of video streaming over wireless laneSAT Publishing House
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Analyzing Video Streaming Quality by Using Various Error Correction Methods o...IJERA Editor
Transmission video over ad hoc networks has become one of the most important and interesting subjects of study for researchers and programmers because of the strong relationship between video applications and frequent users of various mobile devices, such as laptops, PDAs, and mobile phones in all aspects of life. However, many challenges, such as packet loss, congestion (i.e., impairments at the network layer), multipath fading (i.e., impairments at the physical layer) [1], and link failure, exist in transferring video over ad hoc networks; these challenges negatively affect the quality of the perceived video [2].This study has investigated video transfer over ad hoc networks. The main challenges of transferring video over ad hoc networks as well as types of errors that may occur during video transmission, various types of video mechanisms, error correction methods, and different Quality of Service (QoS) parameters that affect the quality of the received video are also investigated.
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Cloudsim quality-differentiated video multicast in multirate wireless networks
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QUALITY-DIFFERENTIATED VIDEO MULTICAST IN MULTIRATE
WIRELESS NETWORKS
ABSTRACT:
Adaptation of modulation and transmission bit-rates for video multicast in a multirate wireless
network is a challenging problem because of network dynamics, variable video bit-rates, and
heterogeneous clients who may expect differentiated video qualities. Prior work on the leaderbased schemes selects the transmission bit-rate that provides reliable transmission for the node
that experiences the worst channel condition.
However, this may penalize other nodes that can achieve a higher throughput by receiving at a
higher rate. In this work, we investigate a rate-adaptive video multicast scheme that can provide
heterogeneous clients differentiated visual qualities matching their channel conditions. We first
propose a rate scheduling model that selects the optimal transmission bitrate for each video
frame to maximize the total visual quality for a multicast group subject to the m inimum-visualquality-guaranteed constraint.
We present a practical and easy-to-implement protocol, called QDM, which constructs a clusterbased structure to characterize node heterogeneity and adapts the transmission bit-rate to network
dynamics based on video quality perceived by the representative cluster heads. Since QDM
selects the rate by a sample-based technique, it is suitable for real-time streaming even without
any preprocess. We show that QDM can adapt to network dynamics and variable video-bit rates
efficiently, and produce a gain of 2-5 dB in terms of the average video quality as compared to the
leader-based approach.
