Adaptive Forward Error Correction (AFEC) based Streaming using RTSP and RTP

Networking of MPEG-4 content is the topic of ongoing standardization efforts in the ISO MPEG and IETF. In this paper, we describe a complete architecture for the transport of MPEG-4 content over the Internet. The MPEG-4 concept of separation between applications and delivery mechanism is preserved. The use of well-established Internet protocols, such as the real time protocol (RTP) and the real time streaming protocol (RTSP) allows for robustness and flexibility in view of interoperability and future extensions. In particular, we present an original proposal for the mapping of MPEG-4 specific signaling primitives onto RTSP functions.

Network high definition video applications such as video calls and videoconferences have been increasingly developed recent years. When congestions occur and network environment becomes unstable, the network applications have to deal with such issues like delay, packet loss and bandwidth constraints. In this paper, we describe a high definition H.264/AVC video transmission system with network adaptive function based on real-time transport protocol (RTP) and real-time transport control protocol (RTCP). The adaptive system is composed of three components: 1) transmission management (TM) which focuses on network state monitoring, bandwidth allocating and transmission rate control; 2) a feedback-based adaptive forward error correction (AFEC) scheme using Reed Solomon (RS) code; 3) adaptive video encoding (AVE) that adjusts the bitrate of video streaming according to the bandwidth constraint information offered by TM. In our paper, delay, packet loss and bandwidth constraints are generated by the network bottleneck and congestions. Hence, the main idea is to enhance the bitrate of video streaming adapt to the bandwidth constraints. In addition, we integrate AFEC with RTCP to feedback bandwidth status and make the adaptive video streaming more robust under packet loss environment. Here we call it interactive adaptive forward error correction (IAFEC). The test result shows IAFEC can be adaptive to strict bandwidth constraints and high packet loss rates.

Online video transmissions over wireless networks are rising in popularity and have already become part of our daily life. In the meantime, it is necessary to address a number of challenges ranging from the scarce resources, time-varying, and high error rates, to the fluctuating bandwidth, unveiling the need for an adaptive mechanism to ensure a good video transmission. Adaptive Forward Error Correction (FEC) techniques with Quality of Experience (QoE) assurance are appropriate to deliver QoE-aware video data to wireless users in dynamic and high error rates networks. This paper proposes an adaptive Video-aware FEC and Fuzzy Logic-based mechanism to shield realtime video transmissions against packet loss in wireless networks, improving both user experience and the usage of resources. The benefits and drawbacks of the proposed mechanism compared with exiting work are demonstrated through simulations and assessed with QoE metrics.

This memorandum defines the Real-Time Streaming Protocol (RTSP) version 2.0, which obsoletes RTSP version 1.0 defined in RFC 2326.RTSP is an application-layer protocol for the setup and control of the delivery of data with real-time properties.RTSP provides an extensible framework to enable controlled, on-demand delivery of real-time data, such as audio and video.Sources of data can include both live data feeds and stored clips.This protocol is intended to control multiple data delivery sessions; provide a means for choosing delivery channels such as UDP, multicast UDP, and TCP; and provide a means for choosing delivery mechanisms based upon RTP (RFC 3550).

Unmanned aerial vehicles (UAV) are rising in popularity together with video applications for both military and civilian use. Because of that, it is necessary to address a set of challenges related to the device movement, scarce resources as well as high error rates, making evident the need for an adaptive mechanism to strengthen video transmissions. Adaptive Forward Error Correction (FEC) techniques are known to be suitable to enhance the Quality of Experience (QoE) of video transmitted over error-prone wireless networks with high mobility. This book chapter proposes an adaptive video-aware FEC mechanism that uses motion vectors details to improve real-time UAV video transmissions, providing both higher user experience and better usage of resources. The benefits and drawbacks of the proposed mechanism along with the related work are analysed and put up for test through simulations and evaluated using QoE metrics.

This document describes several Network Address Translator (NAT) traversal techniques that were considered to be used for establishing the RTP media flows controlled by the Real-Time Streaming Protocol (RTSP). Each technique includes a description of how it would be used, the security implications of using it, and any other deployment considerations it has. There are also discussions on how NAT traversal techniques relate to firewalls and how each technique can be applied in different use cases. These findings were used when selecting the NAT traversal for RTSP 2.0, which is specified in a separate document.

The Active Service Environment Management system (ASEMA) provides best possible multimedia service experience to end user. One of the main aspects of the ASEMA is to provide a variable live streaming service to the end users of the ASEMA. The ASEMA implements this through dynamic change in the properties of the video stream delivered to the end user's end device. The live video stream used in the ASEMA is delivered to the end users is in MPEG 4 video format. The video itself is streamed on top of the real time protocol (RTP) and the parameters are negotiated with the real time streaming protocol (RTSP) before the streaming commences. The research problem of this is to provide easy solution for QoS measurements in networks that are closed nature. The research is based on the constructive method of the related publications and the results are deducted from the constructed quality of service management of the ASEMA system. The management is founded on the measuring of the receiving and sending bit rate values in both ends, in the sending end and in the receiving end. If a fluctuation in the values are detected the video stream's properties are changed dynamically.

This paper introduces Adaptive and Reliable Forward Error Correction (AR_FEC), a novel mechanism that is designed to ensure reliable and efficient real-time video delivery for Unmanned Aerial Vehicles (UAVs). UAVs communicate using wireless channels that are inherently unreliable. AR_FEC is an application-layer solution that is inspired by edge computing. It incorporates several elements, specifically, adaptive Forward Error Correction (FEC), dynamic video quality, and Unequal Error Protection (UEP). AR_FEC dynamically adjusts the number of redundancy frames per video Group of Picture (GoP) based on packet loss rate, recent average round-trip times, and cross-layer information such as bandwidth usage and network traffic load. Moreover, AR_FEC reacts to congestion via a dynamic video quality algorithm. By adaptively determining suitable redundancy for the video I-frames and adjusting video quality, significant improvements are achieved. Comprehensive simulations demonstrate that the proposed AR_FEC protocol offers excellent performance for the number of delivered frames, latency, throughput, and delivery of frames, within the delay constraints for real-time multimedia streaming from UAVs.

To facilitate learning with video streaming, a transport protocol that can send video is needed, such as HTTP (Hyper Text Transfer Protocol) or RTSP (Real Time Streaming Protocol). Both protocols have their respective advantages and disadvantages when sent over a MANET network. One of them is that the throughput on RTSP is greater but the use of memory is more, this is inversely proportional to the RTSP protocol. In this study, the delay value in scheme 1 HTTP and RTSP protocols has an average delay of 23.225 seconds and 19.075 seconds. The throughput has an average value of 699.165 kbps and 802.656 kbps. Packet loss has an average value of 0.428% and 17.9%. For the use of transmit power nodes have an average of -33 dBm and -31.25 dBm. Memory usage has an average value of 108.46 Mb and 149.6 Mb.While in scheme 2 the delay values for HTTP and RTSP protocols are 28 seconds and 26.1 seconds on average. Throughput 1186,803 kbps and 1316,076 kbps. Packet loss has an average value of 0.0325% and 18.69%. On the use of transmit power nodes have an average of -34 dBm and -32 dBm. Memory usage has an average value of 107.525 Mb and 154.275 Mb.

Chapter 16 - Video Communication Networks

Session setup delay in Packet Switched Streaming (PSS) services over Third Generation (3G) wireless networks is impacted by Real‐Time Streaming Protocol (RTSP) and Session Description Protocol (SDP) signalling exchange and negotiation, as well as media buffering at the terminal before playback. The paper discusses PSS session setup delay over 3G, and proposes two RTSP and SDP protocol extensions to reduce this delay, namely: RTSP Early Setup and usage of SDP Templates. The rationale behind this proposal is presented, particularly when a Secondary Packed Data Protocol Context (PDP‐Context) is used to support media delivery with Quality of Service (QoS) support. The RTSP Early Setup mechanism facilitates pipelining of RTSP messages and early trigger of Secondary PDP‐Context setup. The SDP Template mechanism proposes using a generic procedure to avoid transmission of frequently used SDP fields. Copyright © 2006 John Wiley & Sons, Ltd.

In response to time-varying network loads, the proposed adaptive bandwidth-constrained media-specific forward error correction (FEC) mechanism for voice over IP (VoIP) attempts to maximise the perceived voice quality at the receiver by switching between coding algorithms while maintaining a constant source bit rate. Its inherent fixed bandwidth nature alloys the worries of network overloading caused by additional redundancies. Besides that, during low network traffic, the mechanism adopts a better speech coding scheme with a lower level of redundancy to achieve better voice quality and to reduce the overall latency. Typical voice traffic accumulated through Internet measurements is characterised by using the 2-state Markovian (Gilbert) loss model. To evaluate the overall performance of the adaptive mechanism, the cumulative distribution function (CDF) of perceived voice quality is adopted. Preliminary results clearly show that the proposed adaptive mechanism produces a consistent and enhanced voice reception subject to the primary-encoder limitation while maintaining a constant bandwidth.

Video streaming over wireless channel encounters many challenges due to the time-varying characteristics of wireless channels and limited network bandwidth. In this paper, we investigate an adaptive forward error correction (FEC) scheme for streaming the stored MPEG-4 FGS bit-stream from the video server to the clients over wireless channel. In this scheme, the base layer is transmitted reliably and the enhancement layer is protected with unequal error protection (UEP) scheme. Taking the fine-grained characteristics of FGS into account, we propose a decodable rate maximized criterion to optimally allocate the bit rate between the source rate and the channel coding rate and dynamically adapt to the varying network condition. Experimental results show that Compared with fixed unequal error protection (UEP) and equal error protection (EEP), our proposed method can provide a better performance.

In this paper, we explore the convergence of the caching and streaming technologies for Internet multimedia. The paper describes a design for a streaming and caching architecture to be deployed on broadband networks. The basis of the work is the proposed Internet standard, Real Time Streaming Protocol (RTSP), likely to be the de-facto standard for web-based A/V caching and streaming, in the near future. The proxies are all managed by an `Intelligent Agent' or `Broker' - this has been designed as an enhanced RTSP proxy server that maintains the state information that is so essential in streaming of media data. In addition, all the caching algorithms run on the broker. Having an intelligent agent or broker ensures that the `simple' caching servers can be easily embedded into the network. However, RTSP does nor have the right model for doing broker based streaming/caching architecture. The work reported here is an attempt to contribute towards that end.

Este trabalho apresenta uma implementação de um protótipo de sistema de informação para Ambient Assisted Living (AAL) capaz de identificar em tempo real a partir de qualquer câmera com endereçamento IP que implemente o protocolo Real Time Streaming Protocol (RTSP), possíveis quedas em um ambiente monitorado e treinado. Após uma ocorrência de possível queda, o protótipo gera um alerta para um contato de emergência cadastrado.