Network Dimensioning for MPEG-2 Video Communications Using ATM

This chapter discusses various issues related to the shaping of Motion Picture Experts Group (MPEG) video for generating constrained or controlled variable bit rate (VBR) data streams. MPEG-2 defines a set of standards for coding and compression of digital video. VBR video can offer constant picture quality without incorporating too much processing overhead in the network or transmission system’s architecture. In addition, they can offer substantial (20% to 50%) savings in both storage and transmission bandwidth requirements compared to constant bit rate (CBR) video. Either source coding or encoder’s output shaping or a combination of both can be used for adapting the MPEG-2 video streams for transmission over real-time VBR (rt-VBR)-type asynchronous transfer mode (ATM) channel.

This paper presents a dynamic bandwidth allocation system for real-time variable bit rate (VBR) video transport in asynchronous Transfer mode (ATM) networks. This system takes advantage of scene changes in the video trace on a scale larger than a second, and it adapts the bandwidth as needed. An improvement on efficiency is achieved by assigning bandwidth for the transport of VBR video and having more than one predictor in parallel with different prediction horizons, hence this scheme reduces the processing time for the bandwidth adaptation with no significant degradations on the queue statistics. The link capacity required for a specific session is a function of the input traffic, which is characterized by its spectral characteristic. In particular, we use the low frequency band of the power spectrum, which is extracted from the stochastic input by a low pass filter. The predictor is a neural network (NN) called ”Pi-Sigma Network”, and the output of this predictor is interpreted according to the prediction horizon in use.

For video sources the Moving Picture Experts Group (MPEG) compression scheme has become the defacto standard for video compression since then. However, even with the huge reduction of bits that MPEG compression provides, it does not smooth the video traffic. Indeed the variable bit rate (VBR) MPEG compression algorithm guarantees that the MPEG stream will be bursty. A service, where an asynchronous transfer mode (ATM) client requests and receives from an ATM server VBR MPEG coded video sequences, is considered. An algorithm for streaming VBR MPEG coded video delivery over ATM networks, which dynamically allocates the transmission parameters, is proposed. A scheme for optimal choice of the prediction window's size is also presented. The results obtained show that the proposed dynamic allocation algorithm can provide an efficient solution for VBR MPEG coded video transport with guaranteed quality of service (QoS) over ATM networks.

One of the most important components of an Asynchronous Transfer Mode (ATM) net- work is the switch. Switch design is not a part of the ATM standards so vendors use a wide variety of techniques to build their switches. In this paper, we present experimental results of switching and multiplexing real-time Variable Bit Rate (VBR) digital video traffic (JPEG, MPEG-1, and MPEG-2) through two different ATM switch architectures. Real-time VBR traffic, such as digital video, is particularly interesting due to its high demands in terms of bandwidth, real-time delivery and processing requirements. Our ex- periments show that the 'fastest' switches, i.e., lowest latencies, do not necessarily perform better when transmitting VBR video. The impact of the high speed network components' characteristics, such as switch fabric architecture, buffering strategies, and higher layer transport protocols (i.e., UDP, TCP/IP), are illustrated through the experimental results.

The efficient transportation of real-time variable bit rate (VBR) video traffic in high-speed networks has been an area of active research. The VBR video traffic characteristics having heavy tail distribution, high variance and correlation properties are quite complex. These characteristics of VBR video (MPEG) traces are studied and a new traffic model for VBR video is proposed. A modulating Markov chain model is employed in which each state represents the I, B, P frames (pictures) of a group of pictures (GOP). From the video traces, we classify the scenes (collection of GOPs) into high- and low-activity scenes, based on the average number of bits generated during the scenes. The scene activity is modeled by an auxiliary Markov chain wherein each state represents the degree of activity (high/low). The transitions of the auxiliary Markov chain represent scene changes of a video sequence. The bit generation during a low-activity scene is modeled by independent AR processes for I, P, B frames. The cross-correlation with the I frames is taken into account by the AR(1) processes for the P and B frames during the high-activity scenes. The traffic thus generated by the model is analyzed and its characteristics are found to be in close agreement with those exhibited by the real traces. The proposed model is quite flexible in order to model scene changes and the autocorrelation characteristics that are common to all packetized broadcast video sequences. The parameters of the scene changes in the proposed traffic model can be appropriately tuned, so that, even the teleconferencing video traffic that involves few scene changes, can be modeled.

Accurate prediction of variable bit rate (VBR) video traffic can be used to improve the network utilization efficiency while supporting guaranteed QoS requirements of VBR video. On-line prediction algorithms have been proposed in the literature to forecast real-time VBR video traffic for dynamic bandwidth allocation. In this paper, we survey a number of algorithms both in time domain and wavelet domain for video traffic prediction. The features of the existing algorithms are summarized, and on the basis of it we propose a time-domain and a wavelet-domain normalized least mean square (NLMS) based adaptive prediction scheme respectively. Our proposed time-domain scheme combines the separation and differential techniques in the literature to reduce short-term bit rate variation of VBR video traffic and smooth the data for more accurate perdition. Our proposed wavelet-domain prediction scheme uses the a trous wavelet transform instead of conventional decimated wavelet transform to improve the prediction accuracy by exploiting the redundant information in the wavelet transform coefficients. Simulations using three half-an-hour long full-motion moving picture experts group (MPEG) video traces show that our proposed methods can achieve better performance than those in the literature

The efficient transportation of real-time variable bit rate (VBR) video traffic in the high-speed networks has been an area of active research. The VBR, video traffic characteristics having heavy tail distribution, high variance and correlation properties are quite complex to be captured by a single traffic model. These characteristics of VBR video (MPEG) traces are further examined. While many methods have been proposed in the literature focusing on various aspects of the VBR video traffic characteristics and their impact on the traffic management, a wider perspective of various issues involved in the efficient transportation of VBR video traffic with high utilization of network resources is imperative. This paper reviews proposed traffic management methods from the literature, summarizes the relevant issues, and proposes an integrated framework addressing those issues. The functionalities of various entities of the integrated framework and future research directions are outlined.

A fuzzy approach to MPEG video transmission in ATM networks

This paper presents a general traffic control framework for Asynchronous Transfer Mode (ATM) networks with its performance evaluation. The proposed traffic control scheme can incorporate all the recently considered ATM service classes including Constant Bit Rate (CBR), real time Variable Bit Rate (rtVBR), non-real time Variable Bit Rate (nrVBR), Available Bit Rate (ABR) and Unspecified Bit Rate (UBR) services. The control is based on a complete buffer partitioning architecture and on the associated buffer scheduling rule with adaptive weighting functions. We present, the formulation of the traffic control as an optimization problem in a 3-dimensional Quality of Service (QoS) state space. A solution approach based on dynamic programming is also suggested. A comprehensive performance evaluation of the method has been performed based on simulations and results are presented with several examples. The QoS dependence on CBR load, VBR load, VBR burstiness, UBR load are investigated and results are demonstrated with explanations.

This paper is concerned with an intelligent application of Moving Picture Expert Group (MPEG) video transmission over IEEE 802.15.4 – ZigBee. MPEG Variable Bit Rate (VBR) video is data hungry and presents excessive time delay and data loss over a wireless communication. Conventional rate policing such as generic cell rate algorithm is inadequate to sufficiently regulate transmission of VBR data sources over bandwidth limited ZigBee. Therefore, it is impossible to transmit MPEG VBR video over ZigBee channel. A buffer entitled ‘traffic-shaping buffer’ is introduced to prevent excessive overflow of MPEG video data over the ZigBee channel. A new Neural-Fuzzy (NF) scheme is developed to adjust the traffic-shaping buffer output rate to eliminate unacceptable delay or loss of the VBR encoded video and to conform the data to the token-bucket's contract prior entering the ZigBee channel. A Rule-Based Fuzzy (RBF) scheme is developed to monitor the data rate entering the traffic-shaper, in order to prevent either saturation or starvation of the buffer. The simulation results show that the use of the NF scheme and the RBF scheme enables MPEG VBR video to be transmitted over ZigBee.

The overall aim of the paper is concerned with transmission of a digital video signal over an asynchronous transfer mode (ATM) network, using a self-organizing fuzzy (SOF) controller. In ATM a traffic-shaping buffer is used to prevent excessive back-to-back cells being generated during the peak transmissions of Moving Picture Expert Group (MPEG) variable bit rate (VBR) data sources. The VBR data sources are unpredictable and have substantial variations in bit rate, which could result in data loss and therefore image quality degradation. In this research, a self-organizing fuzzy controller is applied to digital video to eliminate excessive delay or loss at the user network interface. A self-organizing fuzzy controller adjusts the traffic-shaping buffer output rate frame by frame to enable the VBR encoded video to conform to the leaky bucket's contract. A rule-based fuzzy (RBF) controller regulates the average arrival rate to the traffic-shaping buffer to prevent either overflow or starvation of the buffer on a group of picture (GOP) by GOP basis. The computer simulation results demonstrate that the use of a SOF controller reduces excessive delay and data loss at the user network interface as compared with a conventional policing mechanism in ATM.

All traffic models for MPEG-like encoded variable bit rate (VBR) video can be categorized into (i) data rate models (DRMs), and (ii) frame size models (FSMs). Almost all proposed VBR traffic models are DRMs. Since DRMs generate only data arrival rate, they are good for estimating average packet-loss and ATM buffer over-flowing probabilities, but fail to identify such details as percentage of frames affected. FSMs generate sizes of individual MPEG frames, and are good for studying frame loss rate in addition to data loss rate. Among three previously proposed FSMs: (i) one generates frame sizes for full-length movies without preserving GOP-periodicity; (ii) another generates frame sizes for full-length movies without preserving size-based video-segment transitions; and (iii) the third generates VBR video traffic for news videos from scene content description provided to it presupposing a proper segmentation. In this paper, we propose two segmentation techniques for VBR videos - (a) Equal Number of GOPs in all shot classes (ENG), and (b) Geometrically Increasing Interval Lengths for shot classes (GIIL). Each technique partitions the GOPs in the video into size-based shot classes. Frames in each class produce three data-sets one each for I-, B-, and P-type frames. Each of these data-sets can be modeled with an axis shifted Gamma distribution. Markov renewal processes model interclass transitions. We have used QQ plots to show visual similarity of model-generated VBR video data-sets with original data-set. Leaky-bucket simulation study has been used to show similarity of data and frame loss rates between model-generated videos and original video. Our study of frame-based VBR video revealed GIIL segmentation technique separates the I-, B-, and P- frames in well behaved shot classes whose statistical properties can be captured by Gamma-based models.

A Review on Bandwidth Utilization for Bursty Traffic in Asynchronous Transfer Mode Networks

This paper is concerned with transmission of a moving picture expert group (MPEG) video stream over a Bluetooth channel, using an adaptive neuro-fuzzy technique. MPEG variable bit rate (VBR) video sources over a network generally experience long delay and unacceptable data loss, due to high variations in bit rate. Furthermore, transmission rate could be unpredictable in a Bluetooth network due to interferences by other wireless devices or general Bluetooth channel noises. Subsequently, it is almost impossible to transmit VBR data sources over Bluetooth without excessive delay or data loss. In this work, an adaptive scheme is introduced so that the controller may adjust itself to the current state of the system under control. This paper utilizes a traffic-shaping buffer to prevent excessive back-to-back transmissions of MPEG VBR data sources. A novel adaptive neuro-fuzzy scheme regulates the output rate of the buffer to ensure that the video stream from the host conforms to the traffic conditions of the Bluetooth channel during the transmission period. The computer simulation results show that the use of the neuro-fuzzy controller reduces excessive delay and data loss at the host-controller-interface, as compared with a conventional VBR video transmission and a rule-based fuzzy controller (RBF1) in Bluetooth

Recently, there has been much interest in sending video over Broadband Integrated Services Digital Networks (B-ISDN) using Asynchronous Transfer Mode (ATM). ATM affords a flexible multiplexing and switching capability for integrated delivery of bursty traffic. As such, video can be transported either with a constant bit-rate (CBR) or with a variable bit-rate (VBR). VBR video has several potential advantages over traditional CBR video: improved image quality and shorter delay. In addition, through statistical multiplexing, improved channel allocation may be obtained compared to CBR transport.