针对FlashP2P技术,对其RTMFP协议进行了深入分析,提出了一种基于RTMFP包检测的FlashP2P流量识别算法,并采用该算法对国内主流视频网站的FlashP2P流进行了有效的识别.在此基础上,对FlashP2P流量特征进行分析并证明其具有自相似性.最后,提出了一种基于ARIMA模型的经验模式分解预测自相似网络流量的方法,而且进行了仿真验证.结果表明,该模型不仅降低了算法的复杂度,并且对短期预测精度较高.
The RTMFP protocol of FlashP2P technique is analyzed in detail and a FlashP2P traffic recognition algorithm based on RTMFP packet detection is proposed.The algorithm is used to effectively identify the FlashP2P streams of the domestic mainstream video sites.On this basis,the characteristics of FlashP2P flow are analyzed and their self-similarity is proved.Finally,based on the empirical mode decomposition of the ARIMA,we build a model to predict the self-similar network traffic.The simulation results show that the model not only reduces the complexity of the algorithm but also has high short-term forecast accuracy.