Modeling and Simulation of Self-Similar Traffic in Wireless IP Networks

Abstract

The article examines self-similar properties of real telecommunications network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Simulation with stochastic and long range dependent traffic source models is performed, and the algorithms for buffer overflow simulation for finite buffer single server model under self-similar traffic load SSM/M/1/B are explained. The algorithms for modeling fixedlength sequence generators that are used to simulate self-similar behavior of wireless IP network traffic are developed and applied. Numerical examples are provided, and simulation results are analyzed.

Peculiarities and Applications of Stochastic Processes with Fractal Properties

“…Recently, interest in the class of non-stationary processes that have a fractal nature has deepened [ 1 , 2 , 3 , 5 , 6 , 7 , 8 , 9 , 10 , 14 , 18 , 19 ].…”

“…Analyses of network telecommunication traffic result in time series (TS) analyses most widely used in traditional methods of statistically analyzing random variable functions. Alongside with traditional methods the signal processing methods based on fractal and wavelet-transformations [ 5 , 7 , 9 , 10 , 14 , 18 , 19 ], have seen more widespread use in recent years. The first of these analyses is specifically concerned with the identification of fractal properties that allow time series’ to be attributed to predetermined models.…”

“…Telecommunication network traffic exhibits self-similar properties over a wide range of time scales that are very different to the properties of traditional models. Self-similar models are appropriate for telecommunication network traffic, as they have the capacity to estimate network performance/quality, allocate resources, and ensure quality of service [ 9 ].…”

“…This article examines the features of stochastic process models with fractal properties and their applications in some important areas. These areas include: sensors and measuring systems [ 4 , 5 ], navigation and motion controls [ 6 , 7 ], telecommunication systems [ 3 , 8 , 9 ], and flaw detection technologies [ 10 , 11 ].…”