It is reported and widely believed that Web traffic exhibits heavy tail distributions and is one of the major causes of long range dependence observed in the Internet traffic.

In this talk, we re-examine these issues and provide some new insights. In particular, we show that such heavy tail distributions are not the most appropriate for characterizing traffic of many Web servers. Instead, light tail and subexponential tail distributions are frequently observed which can not cause long range dependence, yet coexist with the long range dependence in the observation. Though there are results in the literature for self-similar arrival process with constant service rates, or for subexponential service times with i.i.d. arrival process, how the server performance would
be influenced by the coexistence of long range dependent arrival process and subexponential service times is an open question. We present asymptotic queueing analysis of such systems and show the different dominant components that influence server performance under different conditions. Simulation resutls are then presented for comparison.

This is joint work with Zhen Liu, Mark S. Squillante, Li Zhang and Naceur Malouch.