Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
A multifractal wavelet model with application to network traffic
IEEE Transactions on Information Theory
A Markovian approach for modeling packet traffic with long-range dependence
IEEE Journal on Selected Areas in Communications
A prediction method of network traffic using time series models
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
| Hi-index | 0.00 |
Traffic characterization is of great importance in the analysis and dimensioning of modern telecommunication networks. In this paper, the microdynamics of some sets of traffic are investigated. The approach we use to study the microdynamics is Poissonification, which is a way of transforming a point process into a Poisson process locally. We want to gain basic knowledge of how the traffic behaves on smaller time scales, but we also want to see if there are any effects when the traffic is fed into a queue. As an application, Poissonification can be used when modeling is done with a doubly stochastic Poisson process to find the time scale where we no longer have the doubly stochastic behavior. Three different traffic traces were analyzed in this paper. The results show that provided the Poissonification is carried out at a sufficiently small time scale, the performance characteristics are not decisively changed and this gives a guide to choosing the time scale at which to start traffic modeling.