Analysis of Dynamic Performance in IP/WDM Networks under Self-similar Traffic

摘要

In this paper, we study the dynamic performance of self-similar traffic under different integrated routing algorithms in IP/WDM networks for the first time. The self-similar traffic is generated by FFT-FGN method characterized by three parameters (H, M, V) namely Hurst parameter, Mean Value and variance Value. Through extensive simulation in three respective network topologies, the effects on the dynamic performance by the parameters of self-similar traffic (Hurst, Mean, Variance ) and the parameter of network (connectivety of the topologies) are analyzed, we know that the network blocking probability increases with the rise of H and V due to the bursty of traffic becomes more obvious. And the increasing of M makes the network blocking probability higher because of increasing of traffic volume. Moreover different IR algorithms have different performance using self-similar model, and integrated min-hop routing (IMH) algorithm outperforms the others. All these trends are not changed with the connectivity of the network topologies. In addition, in order to know the difference of dynamic performance between the Poisson and self-similar model, we compare the performance of the two modes under the same condition. Simulation results show that network blocking probability of self-similar traffic is lager than that of Poisson due to the property of long-rage dependence of self-similar traffic.