최근 몇 년 동안 몇몇 환경에서 트래픽 패턴이 Poisson 패턴보다 Self-similar 패턴에 더 가깝다는 것이 입증되어 왔다. 본 논문에서는 이러한 Self-similar 확률과정의 정의 및 트래픽의 특성, 그리고 최근 논문들에서 보고된 사례에 대해서 고찰해 봄으로써, 실제의 이동전화 데이터 트래픽 특성에 적합한지를 응용하고자 한다.
The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction. However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially from the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish yon that it makes out about the characteristics of actual data traffic more easily.
