ABSTRACT
In this paper an algorithm based on fractional Brownian motion is used to simulate network traffic. The simulated traffic is compared with real network traffic and the results from the comparison show that they are similar to each other, as the difference between the relative errors of the Hurst parameter of the simulated traffic and the real traffic is less than 2%. Therefore this algorithm could be used for practical simulation research.
- Fowler T. A Short Tutorial on Fractals and Internet Traffic. The Telecommunications Review, Vol. 10, Mitretek Systems, McLean, VA, pp. 1--14, 1999.Google Scholar
- Jeong H.-D., D. McNickle and K. Pawlikowski. A Generator of Pseudo-random Self-Similar Sequences Based on SRA. Technical Report TR-COSC 9/98, Department of Computer Science, University of Canterbury, Christchurch, New Zeland, 1998.Google Scholar
- Jeong H.-D., D. McNickle and K. Pawlikowski. A Comparative Study of Three Self-Similar Teletraffic Generators. In Proceeding of 13th European Simulation Multiconference, Warsaw, Poland, vol. 1, pp. 356--362, 1999.Google Scholar
- Lau W-C, A. Erramilli, J. Wang and W. Willinger. The Random Midpoint Displacement algorithm and Its Properties. IEEE International Conference on Communications, Vol 1, pp. 466--472, 1995.Google Scholar
- Leland W., M. Taqqu, W. Willinger and D. Wilson. On the Self-Similar Nature of Ethernet Traffic. Computer Communication Review, 23, pp. 183--193, 1993. Google ScholarDigital Library
- Mandelbrot, B., The fractal geometry of nature. W. H. Freeman and Company, New York, 1983.Google Scholar
- Sheluhin, O. Multifractals. Infocommunication applications (In Russian) Goryachaya Linia Publishers, Russia, 2011.Google Scholar
- Sheluhin O. I., S. M. Smolsky and A. V. Osin. Self-Similar Processes in Telecommunications. John Wiley & Sons, England, 2007. Google ScholarDigital Library
- http://ita.ee.lbl.gov/traces/Google Scholar
- Business Week, April 7, 2001.Google Scholar
Recommendations
Fractal Traffic Models for Internet Simulation
ISCC '00: Proceedings of the Fifth IEEE Symposium on Computers and Communications (ISCC 2000)We construct five new fractal traffic models based on the unified framework of Fractal Point processes (FPPs), and analyze their asymptotic statistical properties. Two of them are On-Off types, suitable for characterizing an aggregate fractal traffic ...
Fractal and multifractal analysis of network teletraffic
CompSysTech '12: Proceedings of the 13th International Conference on Computer Systems and TechnologiesIn the paper is investigated fractal and multifractal properties of the real network traffic, such as Ethernet, TCP, UDP and the simulated fractal (self-similarity) traffic based on the fractional Gaussian noise (FGN) process. The obtained results show ...
A Study Based on Self-Similar Network Traffic Model
ISDEA '15: Proceedings of the 2015 Sixth International Conference on Intelligent Systems Design and Engineering ApplicationsThe traffic model is the core foundation of traffic prediction and network performance evaluation. In order to accurately predict traffic conditions, good flow model must be able to accurately describe the characteristics of the actual flow of the ...
Comments