Modeling and generating realistic background traffic by hybrid approach

Abstract

One of the key challenges in large-scale network simulation is the huge computation demand in fine-grained traffic simulation. Apart from using high-performance computing facilities and parallelism techniques, an alternative is to replace the background traffic by simplified abstract models such as fluid flows. This paper suggests a hybrid modeling approach for background traffic, which combines ON/OFF model with TCP activities. The ON/OFF model is to characterize the application activities, and the ordinary differential equations (ODEs) based on fluid flows is to describe the TCP congestion avoidance functionality. The apparent merits of this approach are (1) to accurately capture the traffic self-similarity at source level, (2) properly reflect the network dynamics, and (3) efficiently decrease the computational complexity. The experimental results show that the approach perfectly makes a proper trade-off between accuracy and complexity in background traffic simulation.