1,354 research outputs found
Self-generated Self-similar Traffic
Self-similarity in the network traffic has been studied from several aspects:
both at the user side and at the network side there are many sources of the
long range dependence. Recently some dynamical origins are also identified: the
TCP adaptive congestion avoidance algorithm itself can produce chaotic and long
range dependent throughput behavior, if the loss rate is very high. In this
paper we show that there is a close connection between the static and dynamic
origins of self-similarity: parallel TCPs can generate the self-similarity
themselves, they can introduce heavily fluctuations into the background traffic
and produce high effective loss rate causing a long range dependent TCP flow,
however, the dropped packet ratio is low.Comment: 8 pages, 12 Postscript figures, accepted in Nonlinear Phenomena in
Complex System
The Dynamics of Internet Traffic: Self-Similarity, Self-Organization, and Complex Phenomena
The Internet is the most complex system ever created in human history.
Therefore, its dynamics and traffic unsurprisingly take on a rich variety of
complex dynamics, self-organization, and other phenomena that have been
researched for years. This paper is a review of the complex dynamics of
Internet traffic. Departing from normal treatises, we will take a view from
both the network engineering and physics perspectives showing the strengths and
weaknesses as well as insights of both. In addition, many less covered
phenomena such as traffic oscillations, large-scale effects of worm traffic,
and comparisons of the Internet and biological models will be covered.Comment: 63 pages, 7 figures, 7 tables, submitted to Advances in Complex
System
A critical look at power law modelling of the Internet
This paper takes a critical look at the usefulness of power law models of the
Internet. The twin focuses of the paper are Internet traffic and topology
generation. The aim of the paper is twofold. Firstly it summarises the state of
the art in power law modelling particularly giving attention to existing open
research questions. Secondly it provides insight into the failings of such
models and where progress needs to be made for power law research to feed
through to actual improvements in network performance.Comment: To appear Computer Communication
On the multiresolution structure of Internet traffic traces
Internet traffic on a network link can be modeled as a stochastic process.
After detecting and quantifying the properties of this process, using
statistical tools, a series of mathematical models is developed, culminating in
one that is able to generate ``traffic'' that exhibits --as a key feature-- the
same difference in behavior for different time scales, as observed in real
traffic, and is moreover indistinguishable from real traffic by other
statistical tests as well. Tools inspired from the models are then used to
determine and calibrate the type of activity taking place in each of the time
scales. Surprisingly, the above procedure does not require any detailed
information originating from either the network dynamics, or the decomposition
of the total traffic into its constituent user connections, but rather only the
compliance of these connections to very weak conditions.Comment: 57 pages, color figures. Figures are of low quality due to space
consideration
The pseudo-self-similar traffic model: application and validation
Since the early 1990¿s, a variety of studies has shown that network traffic, both for local- and wide-area networks, has self-similar properties. This led to new approaches in network traffic modelling because most traditional traffic approaches result in the underestimation of performance measures of interest. Instead of developing completely new traffic models, a number of researchers have proposed to adapt traditional traffic modelling approaches to incorporate aspects of self-similarity. The motivation for doing so is the hope to be able to reuse techniques and tools that have been developed in the past and with which experience has been gained. One such approach for a traffic model that incorporates aspects of self-similarity is the so-called pseudo self-similar traffic model. This model is appealing, as it is easy to understand and easily embedded in Markovian performance evaluation studies. In applying this model in a number of cases, we have perceived various problems which we initially thought were particular to these specific cases. However, we recently have been able to show that these problems are fundamental to the pseudo self-similar traffic model. In this paper we review the pseudo self-similar traffic model and discuss its fundamental shortcomings. As far as we know, this is the first paper that discusses these shortcomings formally. We also report on ongoing work to overcome some of these problems
Traffic measurement and analysis
Measurement and analysis of real traffic is important to gain knowledge
about the characteristics of the traffic. Without measurement, it is
impossible to build realistic traffic models. It is recent that data
traffic was found to have self-similar properties. In this thesis work
traffic captured on the network at SICS and on the Supernet, is shown to
have this fractal-like behaviour. The traffic is also examined with
respect to which protocols and packet sizes are present and in what
proportions. In the SICS trace most packets are small, TCP is shown to be
the predominant transport protocol and NNTP the most common application.
In contrast to this, large UDP packets sent between not well-known ports
dominates the Supernet traffic. Finally, characteristics of the client
side of the WWW traffic are examined more closely. In order to extract
useful information from the packet trace, web browsers use of TCP and HTTP
is investigated including new features in HTTP/1.1 such as persistent
connections and pipelining. Empirical probability distributions are
derived describing session lengths, time between user clicks and the
amount of data transferred due to a single user click. These probability
distributions make up a simple model of WWW-sessions
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