Flow and Congestion Control for Internet Streaming Applications

The emergence of streaming multimedia players provides users with low latency audio and video content over the Internet. Providing high-quality, best-effort, real-time multimedia content requires adaptive delivery schemes that fairly share the available network bandwidth with reliable data protocols such as TCP. This paper proposes a new flow and congestion control scheme, SCP (Streaming Control Protocol) , for real-time streaming of continuous multimedia data across the Internet. The design of SCP arose from several years of experience in building and using adaptive real-time streaming video players. SCP addresses two issues associated with real-time streaming. First, it uses a congestion control policy that allows it to share network bandwidth fairly with both TCP and other SCP streams. Second, it improves smoothness in streaming and ensures low, predictable latency. This distinguishes it from TCP\u27s jittery congestion avoidance policy that is based on linear growth and one-half reduction of its congestion window. In this paper, we present a description of SCP, and an evaluation of it using Internet-based experiments

QoS Based Capacity Enhancement for WCDMA Network with Coding Scheme

The wide-band code division multiple access (WCDMA) based 3G and beyond cellular mobile wireless networks are expected to provide a diverse range of multimedia services to mobile users with guaranteed quality of service (QoS). To serve diverse quality of service requirements of these networks it necessitates new radio resource management strategies for effective utilization of network resources with coding schemes. Call admission control (CAC) is a significant component in wireless networks to guarantee quality of service requirements and also to enhance the network resilience. In this paper capacity enhancement for WCDMA network with convolutional coding scheme is discussed and compared with block code and without coding scheme to achieve a better balance between resource utilization and quality of service provisioning. The model of this network is valid for the real-time (RT) and non-real-time (NRT) services having different data rate. Simulation results demonstrate the effectiveness of the network using convolutional code in terms of capacity enhancement and QoS of the voice and video services.Comment: 10 Pages, VLSICS Journa

An efficient rate control algorithm for a wavelet video codec

Rate control plays an essential role in video coding and transmission to provide the best video quality at the receiver's end given the constraint of certain network conditions. In this paper, a rate control algorithm using the Quality Factor (QF) optimization method is proposed for the wavelet-based video codec and implemented on an open source Dirac video encoder. A mathematical model which we call Rate-QF (R - QF) model is derived to generate the optimum QF for the current coding frame according to the target bitrate. The proposed algorithm is a complete one pass process and does not require complex mathematical calculation. The process of calculating the QF is quite simple and further calculation is not required for each coded frame. The experimental results show that the proposed algorithm can control the bitrate precisely (within 1% of target bitrate in average). Moreover, the variation of bitrate over each Group of Pictures (GOPs) is lower than that of H.264. This is an advantage in preventing the buffer overflow and underflow for real-time multimedia data streaming

QARC: Video Quality Aware Rate Control for Real-Time Video Streaming via Deep Reinforcement Learning

Due to the fluctuation of throughput under various network conditions, how to choose a proper bitrate adaptively for real-time video streaming has become an upcoming and interesting issue. Recent work focuses on providing high video bitrates instead of video qualities. Nevertheless, we notice that there exists a trade-off between sending bitrate and video quality, which motivates us to focus on how to get a balance between them. In this paper, we propose QARC (video Quality Awareness Rate Control), a rate control algorithm that aims to have a higher perceptual video quality with possibly lower sending rate and transmission latency. Starting from scratch, QARC uses deep reinforcement learning(DRL) algorithm to train a neural network to select future bitrates based on previously observed network status and past video frames, and we design a neural network to predict future perceptual video quality as a vector for taking the place of the raw picture in the DRL's inputs. We evaluate QARC over a trace-driven emulation. As excepted, QARC betters existing approaches.Comment: Accepted by ACM Multimedia 201

A Rate Control Model of MPEG-4 Encoder for Video Transmission over Wireless Sensor Network

Recently, multimedia application has a lot of attention in the research community, especially when transmitting video over IEEE 802.15.4 standard. This is due to the capability of providing low complexity with low cost, but still maintaining the quality of video in term of packet received. However, transmitting video over Wireless Sensor Network (WSN) posed a new research challenges with high bandwidth demand and energy constrained of sensor nodes. MPEG-4 video codec is one of the compression techniques that used to decrease the amount of bandwidth required to meet WSN environment. Therefore, video encoding is a useful tool for rate control to control the video bit rate and maintaining the video quality especially in real-time communication applications. Video bit rate is affected by quantization scale, frame rate, and Group of Picture (GOP) size. A rate control model called enhanced Video Motion Classification based (e-ViMoC) model is proposed in this paper to produce the desired bit rate that complies to the IEEE 802.15.4 standard, while at the same time preserving the video quality. The analysis has shown that, the video transmission using e-ViMoC rate control achieves enhancement in delivery ratio, energy consumption and video quality (PSNR) when compared to video transmission using uncompressed video

VStorm: Video Traffic Management By Distributed Data Stream Processing Systems

Recent published work has shown that Quality of Experience (QoE) has become one of the major concerns in the area of large scale multimedia Internet services. Due to the significant increase of video traffic and continuously growing need of video quality experience, the need of a new management platform specifically designed for multimedia traffic can no longer be ignored. Recent studies have been proposed advanced solution that can potentially burden the video streaming framework. On the other hand, we have also witnessed the emergence of large scale distributed stream processing systems. These systems provide real-time results for nearly all types of data streams and computation in a massive scale. In this project, we are going to explore the possibility of deploying distributed data stream processing (DSP) systems in a large-scale multimedia network with dynamically changing Internet resource. In this paper, we are going to use a popular distributed stream processing system, Apache Storm to implement multiple frameworks proposed by recent published work. Simulation results on our frameworks show that implementing complex stream control strategy in DSPs can be efficient and flexible.Ope

Supporting Multimedia Services in the Future Network with QoS-routing

The increasing demand for real-time multimedia applications for groups of users, together with the need for assuring high quality support for end-to-end content distribution is motivating the scientific community and industry to develop novel control, management and optimization mechanisms with Quality of Service (QoS) and Quality of Experience (QoE) support. In this context, this paper introduces Q-OSys (QoS-routing with Systematic Access), a distributed QoS-routing approach for enhancing future networks with autonomous mechanisms orchestrating admission control, per-class overprovisioning, IP Multicast and load-balancing to efficiently support multiuser multimedia sessions. Simulation experiments were carried to show the efficiency and impact of Q-OSys on network resources (bandwidth utilization and packet delay). Q-OSys is also evaluated from a user point-of-view, by measuring well-known objective and subjective QoE metrics, namely Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSM) Video Quality Metric (VQM) and Mean Opinion Score (MOS)

An adaptive system for real-time scalable video streaming with end- to-end qos control

This paper presents a real-time adaptive video streaming system based on the latest standardized video codec H.264/MPEG-4 AVC scalable extension (SVC). The system provides a full MPEG-21 media access framework over heterogeneous networks and terminals with end-to-end QoS control and multimedia adaptation based on SVC. This adaptive streaming system is composed of a server with a real-time SVC encoder, an adaptive network node, and a terminal with appropriate feedback of perceptual quality, network conditions and user preferences for adaptation support. The system facilitates a general content adaptation solution to achieve the end-to-end QoS control

Towards a scalable video interactivity solution over the IMS

Includes bibliographical references (leaves 72-76).Rapid increase in bandwidth and the interactive and scalability features of the Internet provide a precedent for a converged platform that will support interactive television. Next Generation Network platforms such as the IP Multimedia Subsystem (IMS) support Quality of Service (QoS), fair charging and possible integration with other services for the deployment of IPTV services. IMS architecture supports the use of the Session Initiation Protocol (SIP) for session control and the Real Time Streaming Protocol (RTSP) for media control. This study aims to investigate video interactivity designs over the Internet using an evaluation framework to examine the performance of both SIP and RTSP protocols over the IMS over different access networks. It proposes a Three Layered Video Interactivity Framework (TLVIF) to reduce the video processing load on a server