Fast simulation for self-similar traffic in ATM networks
Recently self-similar (or fractal) stochastic processes were proposed as more accurate models of certain categories of traffic (e.g., Ethernet traffic, variable-bit-rate video) which will be transported in ATM networks. Existing analytical results for the tail distribution of the waiting time in a single server queue based on Fractional Gaussian Noise and large deviation theory, are valid under a steady-state regime and for asymptotically large buffer size. However, predicted performance based on steady-state regimes may be overly pessimistic for practical applications. Theoretical approaches to obtain transient queueing behavior and queueing distributions for small buffer size become quickly intractable. The approach we followed in this paper was based on fast simulation techniques for the study of certain rare vents such as cell losses with very small probability of occurrence. Our simulation experiments provide insight on transient behavior that is not possible to predict using current analytical results. Finally, they show good agreement with existing results when approaching steady-state.
|Conference||Proceedings of the 1995 IEEE International Conference on Communications. Part 1 (of 3)|
Huang, C, Devetsikiotis, Michael, Lambadaris, I, & Kaye, A.Roger. (1995). Fast simulation for self-similar traffic in ATM networks. Presented at the Proceedings of the 1995 IEEE International Conference on Communications. Part 1 (of 3).