Self-Similarity Characteristic in Data traffic

Self-Similar특성을 이용한 데이터 트래픽 특성에 관한 연구

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 you that it makes out about the characteristics of actual data traffic more easily.

본 논문에서는 Self-similar 특성을 이용하여 트래픽의 특성을 분석하고, 최근 논문들에서 보고된 사례에 대한 동향과 실제 데이터 트래픽 특성에 대한 분석연구에 대하여 Self-similar 패턴의 분석 결과를 제시한다.