A Self-Similarity Frame Traffic Model Based on the Frame Components in 802.11 Networks

In this study, we analyze the impact of different types of frame traffic on the self-similar behavior of the aggregated frame traffic, collected from the IETF 2005 conference. Our measurement results show that the different types of frame traffic have various impacts on the self-similarity of the aggregated frame traffic in different session periods, and these impacts are simultaneously related with the mean frame size and proportion of the specified frame traffic. Furthermore, a model of self-similarity impact is proposed to describe the self-similarity characteristic relationship between the aggregated frame traffic and different types of frame traffic. This in-depth knowledge of 802.11 wireless network frame traffic can effectively improve the efficiency and performance of network planning, resource management and MAC-layer algorithms.