Variable bit-rate (VBR) compressed video traffic is expected to be a significant component of the traffic mix in integrated services networks. This traffic is hard to manage because it has strict delay and loss requirements while simultaneously exhibiting burstiness at multiple time scales. We show that burstiness over long time scales, in conjunction with resource reservation using one-shot traffic descriptors, can substantially degrade the loss rate, end-to-end delay, and statistical multiplexing gain of a connection. We use large-deviation theory to model the performance of multiple time-scale traffic and to motivate the design of renegotiated constant bit rate (RCBR) service. Sources using

Compressed digital video is one of the most important traffic types in future integrated services networks. However, a network service that supports delay-sensitive video imposes many problems since compressed video sources are variable bit rate (VBR) with a high degree of burstiness. In this paper, we consider a network service that can provide deterministic guarantees on the minimum throughput and the maximum delay of VBR video traffic. A common belief is that due to the burstiness of VBR traffic, such a service will not be efficient and will necessarily result in low network utilization. We investigate the fundamental limits and tradeoffs in providing deterministic performance guarantees to video and use a set of 10 to 90 minute long MPEG-compressed video traces for evaluation. Contrary to conventional wisdom, we are able to show that, in many cases, a deterministic service can be provided to video traffic while maintaining a reasonable level of network utilization. We first conside...

In this paper, we examine the transport and storage of video compressed with a variable bit rate (VBR). We focus primarily on networked video, although we also briefly consider other applications of VBR video, including satellite transmission (channel sharing), playback of stored video, and wireless transport. Packet video research requires careful integration between the network and the video systems; however, a major stumbling block has resulted because commonly used terms are often interpreted differently by the video and networking communities.

Weinvestigate the interaction of congestion control with the partitioning of source information into components of varying importance for variable bit rate packet voice and packet video. High priority transport for the more important signal components results in substantially increased objective service quality. Using a Markovchain voice source model with simple PCM speech encoding and a priority queue, simulation results show a signal-to-noise ratio improvementof45dBwithtwo priorities over an unprioritized system. Performance is sensitive to the fraction of traffic placed in eachpriority, and the optimal partition depends on network loss conditions. When this partition is optimized dynamically, quality degrades gracefully over a wide range of load values. Results with DCT encoded speech and video samples show similar behavior. Variations are investigated such as further partition of low priority information into multiple priorities. A simulation with delay added to represe...

Abstract — In this paper we develop a simple and accurate analytical technique to determine the loss probability at an access node to an asynchronous transfer mode (ATM) network. This is an important problem from the point of view of admission control and network design. The arrival processes we analyze are the Markov-modulated Poisson process (MMPP) and the Markov-modulated fluid (MMF) process. These arrival processes have been shown to model various traffic types, such as voice, video, and still images, that are expected to be transmitted by ATM networks. Our hybrid analytical technique combines results from large buffer theories and quasi-stationary approaches to analyze the loss probability of a finite-buffer queue being fed by Markov-modulated sources such as the MMPP and MMF. Our technique is shown to be valid for both heterogeneous and homogeneous sources. We also show that capacity allocation based on the popular effective-bandwidth scheme can lead to considerable underutilization of the network and that allocating bandwidth based on our model can improve the utilization significantly. We provide numerical results for different types of traffic and validate our model via simulations. Index Terms—Admission control, bandwidth allocation, effective bandwidth, large deviations, loss probability, Markov models, MMPP, queueing analysis. I.

Abstract – One approach to supporting continuous media traffic is via resource reservation at connection establishment time. The shortcomings of this approach are the lack of flexibility in re-negotiating bandwidth parameters after connection establishment and the inability to react to changing server load conditions. In this paper we propose a “selected access scheme” for re-negotiating continuous media delivery from a video-on-demand server. We consider the overall system perspective on resource availability rather than a per-connection resource management scheme. The selected access scheme is combined with data placement strategies for the server to dynamically access desired video frames from a shared storage device. This approach is especially suitable for video data compressed and stored using an inter-frame encoding scheme such as specified by the MPEG standard. Simulation results show that the proposed model can utilize server bandwidth, improve the reliability of playback, reduce the buffering needed, and support VCR-like functions without blocking user access to the storage device. Keywords: Selected access scheme, data placement strategies, scalable service, MPEG, quality of service and VCR-like functions.

Modern telecommunications networks are being designed to accomodate a heterogenous mix of traffic classes ranging from traditional telephone calls to video and data services. Thus, traffic models are of crucial importance to the engineering and performance analysis of telecommunications system, notably congestion and overload controls and capacity estimation. This chapter surveys teletraffic models, addressing both theoretical and computational aspects. It first surveys the main classes of teletraffic models commonly used in teletraffic modeling, and then proceeds to survey traffic methods for computing statistics relevant to the engineering a teletraffic network. 1 INTRODUCTION Traffic is the driving force of telecommunications systems, representing customers making phone calls, transferring data files and other electronic information, or more recently, transmitting compressed video frames to a display device. The most common modeling context is queueing; traffic is offered to a qu...

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: Variable bit rate (VBR) video is expected to be a major source of traffic for the Broadband Integrated Services Digital Network (B-ISDN). To dimension the network, there is a need to predict the network performance. Traffic models are often used as an aid in this process, and many have been proposed as suitable for the modeling of VBR video sources. However, further work is required in the area of verifying the accuracy of models, and little comparison between models is available. In this paper, several of these models are presented and their properties discussed, including their ability to predict accurately different aspects of network performance, with an emphasis on cell loss statistics. Finally, some time is spent reviewing a number of open questions in modeling video streams and their superposition, and the analysis of queueing systems with this kind of input. 1 Introduction Variable bit rate (VBR) video is expected to be a major source of traffic for the Broadband Integrate...

The utility of simulations and analysis heavily relies on good models of network traffic. While network traffic constantly changing over time, existing approaches typically take years from collecting trace, analyzing the data to finally generating and implementing models. In this paper, we describe approaches and tools that support rapid parameterization of traffic models from live network measurements. Rather than treating measured traffic as a timeseries of statistics, we utilize the traces to estimate end-user behavior and network conditions to generate applicationlevel simulation models. We also show multi-scaling analytic techniques are helpful for debugging and validating the model. To demonstrate our approaches, we develop structural source-level models for web and FTP traffic and evaluate their accuracy by comparing the outputs of simulation against the original trace. We also compare our work with existing traffic generation tool and show our approach is more flexible in capturing the heterogeneity of traffic. Finally, we automate and integrate the process from trace analysis to model validation for easy model parameterization from new data.