Dynamic bandwidth allocation based on linear prediction for self-similar traffic = 자기유사 트래픽 환경에서의 선형 예측에 기반한 동적 대역 할당 알고리즘

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 210
  • Download : 0
Recently, self-similar and long range dependent characteristics have received significant attention in network traffic modelling, and it has been known that increasing the link bandwidth is more efficient than increasing the buffer size to meet the required QoS(Quality of Service) for self-similar traffic. So, many studies have been focusing on the estimation of the required bandwidth for self-similar traffic. However, a deterministic bandwidth allocation strategy seems not to be quite effective because of the Noah effect and the Joseph effect. Therefore, we propose the new method to allocate bandwidth dynamically according to the amount of traffic volume. In the proposed method, to avoid frequent estimation of the bandwidth, which is undesirable in the practical situation, we divide the M/G/∞ input process X(t) into two sub-processes, long time scale process $X_l(t)$ and short time scale process $X_s(t)$. For $X_s(t)$ which is Makovian, we allocate a deterministic bandwidth using the effective bandwidth and for $X_l(t)$ which varies (relatively) slowly and hence doesn``t need to be estimated frequently, the required bandwidth is estimated and allocated dynamically using the linear prediction. Throughout simulations we verify that our proposed method performs well to satisfy the required QoS.
Advisors
Hwang, Gang-Ukresearcher황강욱researcher
Description
한국과학기술원 : 응용수학전공,
Publisher
한국과학기술원
Issue Date
2004
Identifier
237839/325007  / 020023073
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 응용수학전공, 2004.2, [ vi, 31 p. ]

Keywords

DYNAMIC BANDWIDTH ALLOCATION; SELF-SIMILAR TRAFFIC; LINEAR PREDICTION METHOD; 선형 예측법; 자기유사 트래픽; 대역 할당

URI
http://hdl.handle.net/10203/42095
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=237839&flag=dissertation
Appears in Collection
MA-Theses_Master(석사논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0