Dynamic bandwidth allocation in ATM networks

Includes bibliographical references.This thesis investigates bandwidth allocation methodologies to transport new emerging bursty traffic types in ATM networks. However, existing ATM traffic management solutions are not readily able to handle the inevitable problem of congestion as result of the bursty traffic from the new emerging services. This research basically addresses bandwidth allocation issues for bursty traffic by proposing and exploring the concept of dynamic bandwidth allocation and comparing it to the traditional static bandwidth allocation schemes

Quality of service over ATM networks

PhDAbstract not availabl

Resource management for multimedia traffic over ATM broadband satellite networks

PhDAbstract not availabl

On the time scales in video traffic characterization for queueing behavior

To guarantee quality of service (QoS) in future integrated service networks, traffic sources must be characterized to capture the traffic characteristics relevant to network performance. Recent studies reveal that multimedia traffic shows burstiness over multiple time scales and long range dependence (LRD). While researchers agree on the importance of traffic correlation there is no agreement on how much correlation should be incorporated into a traffic model for performance estimation and dimensioning of networks. In this article, we present an approach for defining a relevant time scale for the characterization of VER video traffic in the sense of queueing delay. We first consider the Reich formula and characterize traffic by the Piecewise Linear Arrival Envelope Function (PLAEF). We then define the cutoff interval above which the correlation does not affect the queue buildup. The cutoff interval is the upper bound of the time scale which is required for the estimation of queue size and thus the characterization of VER video traffic. We also give a procedure to approximate the empirical PLAEF with a concave function; this significantly simplifies the calculation in the estimation of the cutoff interval and delay bound with little estimation loss. We quantify the relationship between the time scale in the correlation of video traffic and the queue buildup using a set of experiments with traces of MPEG/JPEG-compressed video. We show that the critical interval i.e. the range for the correlation relevant to the queueing delay, depends on the traffic load: as the traffic load increases, the range of the time scale required for estimation for queueing delay also increases. These results offer further insights into the implication of LRD in VER video traffic. (C) 1999 Elsevier Science B.V. Ail rights reserved

QoS provisioning in multimedia streaming

Multimedia consists of voice, video, and data. Sample applications include video conferencing, video on demand, distance learning, distributed games, and movies on demand. Providing Quality of Service (QoS) for multimedia streaming has been a difficult and challenging problem. When multimedia traffic is transported over a network, video traffic, though usually compressed/encoded for bandwidth reduction, still consumes most of the bandwidth. In addition, compressed video streams typically exhibit highly variable bit rates as well as long range dependence properties, thus exacerbating the challenge in meeting the stringent QoS requirements of multimedia streaming with high network utilization. Dynamic bandwidth allocation in which video traffic prediction can play an important role is thus needed. Prediction of the variation of the I frame size using Least Mean Square (LMS) is first proposed. Owing to a smoother sequence, better prediction has been achieved as compared to the composite MPEG video traffic prediction scheme. One problem with this LMS algorithm is its slow convergence. In Variable Bit Rate (VBR) videos characterized by frequent scene changes, the LMS algorithm may result in an extended period of intractability, and thus may experience excessive cell loss during scene changes. A fast convergent non-linear predictor called Variable Step-size Algorithm (VSA) is subsequently proposed to overcome this drawback. The VSA algorithm not only incurs small prediction errors but more importantly achieves fast convergence. It tracks scene changes better than LMS. Bandwidth is then assigned based on the predicted I frame size which is usually the largest in a Group of Picture (GOP). Hence, the Cell Loss Ratio (CLR) can be kept small. By reserving bandwidth at least equal to the predicted one, only prediction errors need to be buffered. Since the prediction error was demonstrated to resemble white noise or exhibits at most short term memory, smaller buffers, less delay, and higher bandwidth utilization can be achieved. In order to further improve network bandwidth utilization, a QoS guaranteed on-line bandwidth allocation is proposed. This method allocates the bandwidth based on the predicted GOP and required QoS. Simulations and analytical results demonstrate that this scheme provides guaranteed delay and achieves higher bandwidth utilization. Network traffic is generally accepted to be self similar. Aggregating self similar traffic can actually intensify rather than diminish burstiness. Thus, traffic prediction plays an important role in network management. Least Mean Kurtosis (LMK), which uses the negated kurtosis of the error signal as the cost function, is proposed to predict the self similar traffic. Simulation results show that the prediction performance is improved greatly as compared to the LMS algorithm. Thus, it can be used to effectively predict the real time network traffic. The Differentiated Service (DiffServ) model is a less complex and more scalable solution for providing QoS to IP as compared to the Integrated Service (IntServ) model. We propose to transport MPEG frames through various service classes of DiffServ according to the MPEG video characteristics. Performance analysis and simulation results show that our proposed approach can not only guarantee QoS but can also achieve high bandwidth utilization. As the end video quality is determined not only by the network QoS but also by the encoded video quality, we consider video quality from these two aspects and further propose to transport spatial scalable encoded videos over DiffServ. Performance analysis and simulation results show that this can provision QoS guarantees. The dropping policy we propose at the egress router can reduce the traffic load as well as the risk of congestion in other domains

Renegotiation based dynamic bandwidth allocation for selfsimilar VBR traffic

The provision of QoS to applications traffic depends heavily on how different traffic types are categorized and classified, and how the prioritization of these applications are managed. Bandwidth is the most scarce network resource. Therefore, there is a need for a method or system that distributes an available bandwidth in a network among different applications in such a way that each class or type of traffic receives their constraint QoS requirements. In this dissertation, a new renegotiation based dynamic resource allocation method for variable bit rate (VBR) traffic is presented. First, pros and cons of available off-line methods that are used to estimate selfsimilarity level (represented by Hurst parameter) of a VBR traffic trace are empirically investigated, and criteria to select measurement parameters for online resource management are developed. It is shown that wavelet analysis based methods are the strongest tools in estimation of Hurst parameter with their low computational complexities, compared to the variance-time method and R/S pox plot. Therefore, a temporal energy distribution of a traffic data arrival counting process among different frequency sub-bands is considered as a traffic descriptor, and then a robust traffic rate predictor is developed by using the Haar wavelet analysis. The empirical results show that the new on-line dynamic bandwidth allocation scheme for VBR traffic is superior to traditional dynamic bandwidth allocation methods that are based on adaptive algorithms such as Least Mean Square, Recursive Least Square, and Mean Square Error etc. in terms of high utilization and low queuing delay. Also a method is developed to minimize the number of bandwidth renegotiations to decrease signaling costs on traffic schedulers (e.g. WFQ) and networks (e.g. ATM). It is also quantified that the introduced renegotiation based bandwidth management scheme decreases heavytailedness of queue size distributions, which is an inherent impact of traffic self similarity. The new design increases the achieved utilization levels in the literature, provisions given queue size constraints and minimizes the number of renegotiations simultaneously. This renegotiation -based design is online and practically embeddable into QoS management blocks, edge routers and Digital Subscriber Lines Access Multiplexers (DSLAM) and rate adaptive DSL modems

Workload Models of VBR Video Traffic and their Use in Resource Allocation Policies

open3The load generated by new types of communications services related to multimedia and video transmission is becoming one of the major sources of traffic in WAN networks. Modeling this type of load is a prerequisite for any performance study. In this paper, we approach the load-characterization problem from a global point of view by analyzing a set of 20 video streams. We developed resource-, subject-, and scene-oriented characterizations of coded video streams.openMANZONI P.; CREMONESI P.; G. SERAZZIManzoni, P.; Cremonesi, Paolo; G., Serazz

A study of the transmission of VBR encoded video over ATM networks.

by Ngai Li.Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.Includes bibliographical references (leaves 66-69).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Video Compression and Transport --- p.2Chapter 1.2 --- Research Contributions --- p.6Chapter 1.2.1 --- Joint Rate Control of VBR Encoded Video --- p.6Chapter 1.2.2 --- Transporting VBR Video on LB Controlled Channel --- p.7Chapter 1.3 --- Organization of Thesis --- p.7Chapter 2 --- Preliminary --- p.9Chapter 2.1 --- Statistical Characteristics of MPEG-1 Encoded Video --- p.9Chapter 2.2 --- Temporal and Spatial Smoothing --- p.14Chapter 2.2.1 --- Temporal Smoothing --- p.14Chapter 2.2.2 --- Spatial Smoothing --- p.15Chapter 2.3 --- A Single Source Control-Theoretic Framework for VBR-to-CBR Video Adaptation --- p.16Chapter 3 --- Joint Rate Control of VBR Encoded Video --- p.19Chapter 3.1 --- Analytical Models --- p.21Chapter 3.2 --- Analysis --- p.27Chapter 3.2.1 --- Stable Region --- p.29Chapter 3.2.2 --- Final Value of the State Variables --- p.33Chapter 3.2.3 --- Peak Values of Buffer-occupancy Deviation and Image- quality Fluctuation --- p.35Chapter 3.2.4 --- SAE of Buffer-occupancy Deviation and Image-quality Fluc- tuation --- p.42Chapter 3.3 --- Experimental Results --- p.43Chapter 3.4 --- Concluding Remarks --- p.48Chapter 4 --- Transporting VBR Video on LB Controlled Channel --- p.50Chapter 4.1 --- Leaky Bucket Access Control --- p.51Chapter 4.2 --- Greedy Token-usage Strategy --- p.53Chapter 4.3 --- Non-greedy Token-usage Strategy --- p.57Chapter 4.4 --- Concluding Remarks --- p.60Chapter 5 --- Conclusions --- p.62Chapter 5.1 --- Joint Rate Control of Multiple VBR Videos --- p.62Chapter 5.2 --- LB Video Compression --- p.63Chapter 5.3 --- Further Study --- p.64Chapter 5.4 --- Publications --- p.65Bibliography --- p.6

Adaptation of variable-bit-rate compressed video for transport over a constant-bit-rate communication channel in broadband networks.

by Chi-yin Tse.Thesis (M.Phil.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 118-[121]).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Video Compression and Transport --- p.2Chapter 1.2 --- VBR-CBR Adaptation of Video Traffic --- p.5Chapter 1.3 --- Research Contributions --- p.7Chapter 1.3.1 --- Spatial Smoothing: Video Aggregation --- p.8Chapter 1.3.2 --- Temporal Smoothing: A Control-Theoretic Study。 --- p.8Chapter 1.4 --- Organization of Thesis --- p.9Chapter 2 --- Preliminaries --- p.13Chapter 2.1 --- MPEG Compression Scheme --- p.13Chapter 2.2 --- Problems of Transmitting MPEG Video --- p.17Chapter 2.3 --- Two-layer Coding and Transport Strategy --- p.19Chapter 2.3.1 --- Framework of MPEG-based Layering --- p.19Chapter 2.3.2 --- Transmission of GS and ES --- p.20Chapter 2.3.3 --- Problems of Two-layer Video Transmission --- p.20Chapter 3 --- Video Aggregation --- p.24Chapter 3.1 --- Motivation and Basic Concept of Video Aggregation --- p.25Chapter 3.1.1 --- Description of Video Aggregation --- p.28Chapter 3.2 --- MPEG Video Aggregation System --- p.29Chapter 3.2.1 --- Shortcomings of the MPEG Video Bundle Scenario with Two-Layer Coding and Cell-Level Multiplexing --- p.29Chapter 3.2.2 --- MPEG Video Aggregation --- p.31Chapter 3.2.3 --- MPEG Video Aggregation System Architecture --- p.33Chapter 3.3 --- Variations of MPEG Video Aggregation System --- p.35Chapter 3.4 --- Experimental Results --- p.38Chapter 3.4.1 --- Comparison of Video Aggregation and Cell-level Multi- plexing --- p.40Chapter 3.4.2 --- Varying Amount of the Allocated Bandwidth --- p.48Chapter 3.4.3 --- Varying Number of Sequences --- p.50Chapter 3.5 --- Conclusion --- p.53Chapter 3.6 --- Appendix: Alternative Implementation of MPEG Video Aggre- gation --- p.53Chapter 3.6.1 --- Profile Approach --- p.54Chapter 3.6.2 --- Bit-Plane Approach --- p.54Chapter 4 --- A Control-Theoretic Study of Video Traffic Adaptation --- p.58Chapter 4.1 --- Review of Previous Adaptation Schemes --- p.60Chapter 4.1.1 --- A Generic Model for Adaptation Scheme --- p.60Chapter 4.1.2 --- Objectives of Adaptation Controller --- p.61Chapter 4.2 --- Motivation for Control-Theoretic Study --- p.64Chapter 4.3 --- Linear Feedback Controller Model --- p.64Chapter 4.3.1 --- Encoder Model --- p.65Chapter 4.3.2 --- Adaptation Controller Model --- p.69Chapter 4.4 --- Analysis --- p.72Chapter 4.4.1 --- Stability --- p.73Chapter 4.4.2 --- Robustness against Coding-mode Switching --- p.83Chapter 4.4.3 --- Unit-Step Responses and Unit-Sample Responses --- p.84Chapter 4.5 --- Implementation --- p.91Chapter 4.6 --- Experimental Results --- p.95Chapter 4.6.1 --- Overall Performance of the Adaptation Scheme --- p.97Chapter 4.6.2 --- Weak-Control verus Strong-Control --- p.99Chapter 4.6.3 --- Varying Amount of Reserved Bandwidth --- p.101Chapter 4.7 --- Conclusion --- p.103Chapter 4.8 --- Appendix I: Further Research --- p.103Chapter 4.9 --- Appendix II: Review of Previous Adaptation Schemes --- p.106Chapter 4.9.1 --- Watanabe. et. al.'s Scheme --- p.106Chapter 4.9.2 --- MPEG's Scheme --- p.107Chapter 4.9.3 --- Lee et.al.'s Modification --- p.109Chapter 4.9.4 --- Chen's Adaptation Scheme --- p.110Chapter 5 --- Conclusion --- p.116Bibliography --- p.11