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	Prediction of Self-Similar Traffic and Its Application in Network Bandwidth Allocation
	Wang, Feng ; Li, Dou ; Zhao, Yuping
	2007
关键词	self-similar traffic chaotic prediction FARIMA bandwidth allocation
英文摘要	In this paper, traffic prediction models based on chaos theory are studied and compared with FARIMA (Fractional Autoregressive Integrated Moving Average) predictors by means of the adopted measurements of predictability. The traffic prediction results are applied in the bandwidth allocation of a mesh network, and the OPNET simulation platform is developed in order to compare their effects. The adopted predictability measurements are inadequate because although the chaotic predictor based on the Lyapunov exponent with worse values of the measurements can timely predict the burstiness of self-similar traffic, the FARIMA predictor forecasts the burstiness with a time-delay. The DAMA (dynamic assignment multi-access) bandwidth allocation strategy combined with the chaotic predictor can provide better QoS performance.; Computer Science, Interdisciplinary Applications; Engineering, Electrical & Electronic; Telecommunications; EI; CPCI-S(ISTP); 0
语种	英语
DOI标识	10.1109/WICOM.2007.495
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/153377]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Wang, Feng,Li, Dou,Zhao, Yuping. Prediction of Self-Similar Traffic and Its Application in Network Bandwidth Allocation. 2007-01-01.

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