Traffic models for UDP streams

Author(s)

Larissa Oliveira Ostrowsky

• Document type: Master's Dissertation
• Press: Campinas, SP.
• Institution: Universidade Estadual de Campinas (UNICAMP). Instituto de Computação
• Defense date: 2005-12-12

Examining board members

Nelson Luis Saldanha da Fonseca; Luan Ling Lee; Edmundo Roberto Mauro Madeira

• Advisor: Nelson Luis Saldanha da Fonseca

Abstract

An important characteristic of the traffic generated by IP protocol is the existence of scaling, since it has great impact on the performance of traffic control mechanism. Therefore, it has been the focus of attention in many researches. The scaling nature of IP traffic has generated lots of controversy. At small time scales the traffic is very irregular and the variability is different from that found in fractal nature at larges scales. There is no general agreement in relation to the nature of the traffic at these small time scales. In the present study, the evidences of multifractality at small time scales were revised via experimental analyses of several real traffic traces. It was concluded that is not possible to generalize that the nature of IP and TCP flows is either monofractal or multifractal, while the nature of the UDP flows is always multifractal. The increasing use of the UDP protocol by real time applications is changing substantially the scaling nature of IP traffic, since this type of traffic does not react to congestion situations. Although there are models for TCP traffic, not much attention has been given to the modeling of UDP flows. Another contribution of this dissertation is a proposition of UDP traffic model, developed from the characterization of the statistics distributions of real traces. This model can reproduce with precision several characteristics of UDP real traffic, including the scaling nature. The model was validated via simulation and the precision of results of the model was compared with the precisions of the MWM and MAP models. Results indicate that the proposed model better reproduces the queue occupation for different storage capacities and service rates then the others evaluated models. The generation of synthetic traces using the adopted model can be realized with low execution times. Thus, the proposed model is acceptable to the dimension of network resources measurement and to provide Quality of Service (AU)