Prediction of Self-Similar Traffic and Its Application in Network Bandwidth Allocation

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 selfsimilar traffic, the FARIMA predictor forecasts the burstiness with a time-delay. The DAMA (dynamic assignment multiaccess) bandwidth allocation strategy combined with the chaotic predictor can provide better QoS performance.

关键词： self-similar traffic chaotic prediction FARIMA bandwidth allocation

作者: Feng Wang Dou Li Yuping Zhao

作者单位: School of Electrical Engineering and Computer Science Peking University Beijing 100871, P. R. China

会议类型: 国际会议

会议名称: 第三届IEEE无线通讯、网络技术暨移动计算国际会议

会议地点: 上海

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）