Recently the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper we examine the mechanisms that give rise to the self-similarity of network traffic. We present a hypothesized explanation for the possible self-similarity of traffic by using a particular subset of wide area traffic: traffic due to the World Wide Web (WWW). Using an extensive set of traces of actual user executions of NCSA Mosaic, reflecting over half a million requests for WWW documents, we examine the dependence structure of WWW traffic. While our measurements are not conclusive, we show evidence that WWW traffic exhibits behavior that is consistent with self-similar traffic models. Then we show that the self-similarity insuch traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in le transfer, the effect of user "think time", and the superimposition of many such transfers in a local area network. To do this we rely on empirically measured distributions both from our traces and from data independently collected at over thirty WWW sites.

A storage model with self-similar input process is studied. A relation coupling together the storage requirement, the achievable utilization and the output rate is derived. A lower bound for the complementary distribution function of the storage level is given. Keywords: Self-similar, fractional Brownian motion, Local Area Network traffic 1 Introduction In a series of papers (e.g. Leland [8], Leland and Wilson [7], Fowler and Leland [4], Leland et al. [9]), researchers from Bellcore have reported and analyzed remarkable Local Area Network (LAN) traffic measurements challenging traditional data traffic modelling. The Bellcore data are both very accurate and extensive in time, and their most striking feature is the tremendous burstiness of LAN traffic at, practically, any timescale. More than that, the statistical analysis has shown that the traffic is self-similar with a surprising accuracy (see Leland et al. [9]). Traditional traffic models based on the Poisson process or, more gener...

Recent traffic measurement studies from a wide range of working packet networks have convincingly established the presence of significant statistical features that are characteristic of fractal traffic processes, in the sense that these features span many time scales. Of particular interest in packet traffic modeling is a property called long-range dependence, which is marked by the presence of correlations that can extend over many time scales. In this paper, we demonstrate empirically that, beyond its statistical significance in traffic measurements, long-range dependence has considerable impact on queueing performance, and is a dominant characteristic for a number of packet traffic engineering problems. In addition, we give conditions under which the use of compact and simple traffic models that incorporate long-range dependence in a parsimonious manner (e.g., fractional Brownian motion) is justified and can lead to new insights into the traffic management of high-speed networks. 1...

In this paper, we characterize wide-area network applications that use the TCP transport protocol. We also describe a new way to model the wide-area traffic generated by a stub network. We believe the traffic model presented here will be useful in studying congestion control, routing algorithms, and other resource management schemes for existing and future networks. Our model is based on trace analysis of TCP/IP widearea internetwork traffic. We collected the TCP/IP packet headers of USC, UCB, and Bellcore networks at the point they connect with their respective regional access networks. We then wrote a handful of programs to analyze the traces. Our model characterizes individual TCP conversations by the distributions of: number of bytes transferred, duration, number of packets transferred, packet size, and packet interarrival time. Our trace analysis shows that both interactive and bulk transfer traffic from all sites reflect a large number of short conversations. Similarly, it shows that a very large percentage of traffic is bidirectional, even for bulk transfer. We observed that interactive applications send significantly different amounts of data in each direction of a conversation, and that interarrival times for interactive applications closely follow a constant plus exponential model. Half of the conversations are directed to a handful of networks, but the other half are directed to hundreds of networks. Many of these observations contradict commonly held beliefs regarding wide-area traffic.

This paper examines the phenomenon of congestion in order to better understand the congestion management techniques that will be needed in high-speed, cell-based networks. The first step of this study is to use high time-resolution local area network (LAN) traffic data to explore the nature of LAN traffic variability. Then, we use the data for a trace-driven simulation of a connectionless service that provides LAN interconnection. The simulation allows us to characterize what congestion might look like in a high-speed, cell-based network. The most

Dynamics of Internet load are investigated using statistics of round-trip delays, packet losses and out-of-order sequence of acknowledgments. Several segments of the Internet are studied. They include a regional network (the Jon yon Neumann Center Network), a segment of the NSFNet backbone and a cross-country network consisting of regional and backbone segments.

As ATM high-speed, cell-relay networks will most likely first make their impact as backbones interconnecting enterprise networks consisting of Ethernet and other LANs, their proper design and control is crucial. Recent studies of high quality, high resolution traffic measurements in Bellcore Ethernets have revealed that this aggregate Ethernet traffic is self-similar ("fractal ") in nature, quite different in "burstiness" features from traffic considered and studied up to now. This paper presents an analytical study of an ATM buffer driven with self-similar traffic. The probability of buffer occupancy is obtained. It is shown that this probability decreases with the buffer size not exponentially, as in traditionally Markovian traffic models, but algebraically . 1 Introduction Recent studies of high-quality, high resolution traffic measurements have revealed a new phenomenon with potentially important ramifications to the modeling, design and control of broadband networks. These includ...

Recently the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper we examine the mechanisms that give rise to self-similar network traffic. We present an explanation for traffic self-similarity by using a particular subset of wide area traffic: traffic due to the World Wide Web (WWW). Using an extensive set of traces of actual user executions of NCSA Mosaic, reflecting over half a million requests for WWW documents, we show evidence that WWW traffic is selfsimilar. Then we show that the self-similarity in such traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user "think time", and the superimposition of many such transfers in a local area network. To do this we rely on empirically measured distributions both from our traces and from data independently collected at over thirty WWW sites. 1 Introduction Understanding the ...

We propose to characterize the burstiness of packet arrival processes with indices of dispersion for intervals and for counts. These indices, which are functions of the variance of intervals and counts, are relatively straightforward to estimate and convey much more information than simpler indices, such as the coefficient of variation, that are often used to describe burstiness quantitatively.

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...