The Impacts of Internet Traffic Variability on Modelling for Large-Scale Broadband Networks
Current methods for modelling network traffic bandwidth do not sufficiently take into account the impacts of traffic variability. The most common models for characterizing network traffic bandwidth are those based on the theories of Illka Norros using fractal Brownian motion  or those based on Frank Kelly's theories using stochastic processes . In both cases the accuracy of the model is dependent on values derived from measured Internet data. These measurements are often sampled at a limited number of points on the network. The task of collecting, evaluating, and constantly updating the data in order to maintain required accuracy is extremely difficult. Data characteristics vary greatly according to time, location on the network, applications in use, and the behavior of users. This paper details the results of a survey examining the degree of network traffic variability on an example broadband network. Impacts are evaluated and the need for adaptive modelling techniques that utilize computational intelligence and adaptive capabilities is proposed.
D. K. Swift and C. H. Dagli, "The Impacts of Internet Traffic Variability on Modelling for Large-Scale Broadband Networks," Proceedings of the Sixth IASTED International Conference on Communications, Internet, and Information Technology, ACTA press, Jul 2007.
Engineering Management and Systems Engineering
Keywords and Phrases
Bandwidth; Brownian Motion; Computation; Fractal Analysis; Fractals; Mathematical Models; Modeling; Stochastic Processes; Traffic Flow
Article - Conference proceedings
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