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IEEE/ACM Transactions on Networking (TON)
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Self-similarity in World Wide Web traffic: evidence and possible causes
Proceedings of the 1996 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
IEEE/ACM Transactions on Networking (TON)
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ACM SIGCOMM Computer Communication Review
A practical guide to heavy tails: statistical techniques and applications
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Time Series Analysis: Forecasting and Control
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Self-similar and Fractal Nature of Internet Traffic Data
ICOIN '01 Proceedings of the The 15th International Conference on Information Networking
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Computer Communications
An engineering approach to dynamic prediction of network performance from application logs
International Journal of Network Management
Characterization of internet traffic using a fractal model
SPPR'07 Proceedings of the Fourth conference on IASTED International Conference: Signal Processing, Pattern Recognition, and Applications
Characterization of Internet traffic using a fractal model
SPPRA '07 Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications
EUNICE'07 Proceedings of the 13th open European summer school and IFIP TC6.6 conference on Dependable and adaptable networks and services
FGN based telecommunication traffic models
WSEAS Transactions on Computers
The practical method of fractal dimensionality reduction based on z-ordering technique
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
A measurement-based study on the correlations of inter-domain Internet application flows
Computer Networks: The International Journal of Computer and Telecommunications Networking
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The self-similar bursty Internet traffic is usually characterized by the Hurst parameter (H). Such a process is also seen to possess fractal characteristics in time described by a parameter (β), with multifractals in most cases. We observe that these highly stochastic traffics have fractals in flow density too, described by a fractal dimension (D), also with the possibiliy of multifractals as in the former. This requires another parameter for the description of Internet traffic, besides the usual self-similarity parameter β or H and the different simulations or models worked out to understand the Internet traffic to reproduce the characteristics as found in the present work. We also find a notable self-similarity feature of the autocorrelations in the data and its aggregates, in all the cases studied.