End-to-end stored FGS video transmission based on adaptive smoothing and TCP-friendly rate control

Yin, Hao; Chen, Lin; Zhang, Qian

doi:10.1109/iccnmc.2003.1243060

Cited by 1 publication

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the aid of the new AAR model, network traffic can be predicted in an online and more precise and efficient way for the purpose to support dynamic traffic forecast, control and resource allocation. As a practical example, our team is now applying the proposed AAR model to an adaptive video transmission [27,28] for performance improvement.…”

Section: Discussionmentioning

confidence: 99%

Network traffic prediction based on a new time series model

Yin

Chen

Berton

et al. 2005

Int J Communication

View full text Add to dashboard Cite

SUMMARYFast and accurate methods for predicting traffic properties and trend are essential for dynamic network resource management and congestion control. With the aim of performing online and feasible prediction of network traffic, this paper proposes a novel time series model, named adaptive autoregressive (AAR). This model is built upon an adaptive memory-shortening technique and an adaptive-order selection method originally developed by this study. Compared to the conventional one-step ahead prediction using traditional Box-Jenkins time series models (e.g. AR, MA, ARMA, ARIMA and ARFIMA), performance results obtained from actual Internet traffic traces have demonstrated that the proposed AAR model is able to support online prediction of dynamic network traffic with reasonable accuracy and relatively low computation complexity.

show abstract

Section: Discussionmentioning

confidence: 99%