基于小波变换和AAR模型的WMN流量预测方法  

Wavelets and AAR Model Based Predicting Algorithm for WMN

作　　者：黄昭文[1] 冯穗力[1] 叶梧[1] 庄宏成[2] 

机构地区：[1]华南理工大学电子与信息学院,广州510640 [2]华为技术有限公司,深圳518129

出　　处：《科学技术与工程》2009年第10期2601-2606,共6页Science Technology and Engineering

基　　金：粤港关键领域重点突破项目(2006010422)资助

摘　　要：在WiMAX Mesh网络中,为了实现对带宽的动态分配和有效利用,需要实时对业务流量进行实时准确预测。WiMAx Mesh网络调度器将根据该预测值进行带宽分配。经分析,现有包括ARMA在内的流量预测方法并不能直接应用于WiMAX Mesh网络流量的预测中。在对WiMAX Mesh网络流量特性的分析基础上,提出了一种基于小波变换和线性自回归模型相结合的WiMAX Mesh网络流量预测方法。该方法首先对流量信号进行降噪,并将该处理结果用于AAR模型预测。利用Auckland大学的流量数据进行仿真,预测精度比自适应ARMA方法提高约2%。方法的预测精度较高,运算量较小,更适合于对WiMAX Mesh网络进行预测。To allocate bandwidth in WiMAX mesh Network dynamically and efficiently, need to predict the realtime traffic volume correctly, which will be sent to the mesh scheduler. The mesh scheduler will grant bandwidth to each Mesh node according to the value. By our study, the current predicting method is fornd, including ARMA, is found to be not so proper for using in WiMAX Mesh Network. First of all, the character of traffic in WiMAX MESH Network is analyzed, then a predicting method based on wavelet transform and AAR model is proposed. With this algorithm, the noise of traffic volume with wavelet transform is decreased, and the result is fed into the AAR model, which will adjust the model argument automatically, to do the predicting job. To verify the algorithm, using the traffic volume data captured in Auckland college into the model, it is found that the algorithm is about 2 percent more accurate than the AARMA model. The simulation result showed that our method has more precise prediction and less computation time, and is more suitable for WiMAX Mesh Network.

关 键 词：WMN WIMAX MESH NETWORK 流量 小波变换 预测 调度 算法 

分 类 号：TN913.2[电子电信—通信与信息系统]