A high fidelity ATM traffic and network simulator

Unger, Brian; Gomes, Fabian; Xiao, Zhonge; Gburzyński, Paweł; Ono-Tesfaye, T.; Ramaswamy, S.; Williamson, Carey; Covington, Alan

doi:10.1145/224401.224763

Cited by 15 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…; comparative evaluation of algorithms for Connection Admission Control (CAC), such as those proposed by Gibbens-Hunt [11] and Norros [12]). What is desired in our ATM network simulator [13] is a traffic source model for which the user can easily set m (the mean bit rate, in bits per second (bps)), a (the Norros variance coefficient, in bit-sec), and H (the Hurst parameter), for such performance studies.…”

Section: Introductionmentioning

confidence: 99%

Synthetic Traffic Generation Techniques For ATM Network Simulations

Williamson

1999

SIMULATION

Self Cite

View full text Add to dashboard Cite

This paper presents a synthetic traffic modeling approach to generate bursty, long-range dependent (LRD) traffic flows for ATM network simulations. The approach uses Fractional-ARIMA processes and a set of mathematical transformations to generate traffic streams with a wide range of user-specified traffic characteristics. With this modeling approach, the user can control the short-range and longrange correlation structure in the generated traffic, as well as the marginal distribution. A description of the techniques is provided, along with a case study illustrating the use of these traffic generation techniques in a capacity planning study for ATM networks.

show abstract

Section: Introductionmentioning

confidence: 99%

Synthetic Traffic Generation Techniques For ATM Network Simulations

Williamson

1999

SIMULATION

Self Cite

View full text Add to dashboard Cite

show abstract

Network modelling and simulation tools

Rahman

Pakštas

Wang

2009

Simulation Modelling Practice and Theory

View full text Add to dashboard Cite

Computer network technologies have been growing explosively and the study in computer networks is being a challenging task. To make this task easy, different users, researchers and companies have developed different network modelling and simulation (MS) tools. These network MS tools can be used in education and research as well as practical purposes. They vary with their characteristics. This paper reviews some of the most important network MS tools developed recently. This paper also shows a classification of the tools used in communications networks.

show abstract