文档介绍：
基于马尔可夫模型的端到端流量预测方法
研究#
蒋定德,聂来森,秦文达*
5
10
(东北大学信息科学与工程学院, 沈阳 110819)
摘要:针对当前通信网络中端端流量预测问题,研究端到端流量的准确预测方法,通过将端
到端流量建模为马尔可夫模型来描述其时间相关性和动态变化特性,并利用测量样本建立马
尔科夫模型的转移概率矩阵,考虑到端到端流量所满足的约束条件,首先预测获得单条端到
端流量流的预测值,然后获得所有端到端流量流的预测,最后通过约束调整获得最终的预测
结果。仿真结果表明所提出的预测方法能精确预测端到端流量并能准确捕获它的动态变化,
与以前的方法相比,具有更好的预测性能和更低的预测误差,并具有明显的性能改善。
关键词:网络流量;马尔可夫模型;流量预测;加权平均;预测误差
中图分类号:TP393
15
On Prediction Approach of End-to-End Traffic Based on
Markov Model
Jiang Dingde, Nie Laisen, Qin Wenda
(College of Information Science and Engineering, Northeastern Universiy, Shenyang 110819)
20
25
30
35
Abstract: For the prediction problem of end-to-end traffic in works,
this paper studies the prediction method about end-to-end traffic. End-to-end traffic is modeled as
the Markov process to describe its temporal correlation and dynamic nature. The measurement
samples about end-to-end traffic are used to build the transition probability matrix of the Markov
model. After considering the constraints met by end-to-end traffic, end-to-end traffic is each
predicted firstly. Then all of end-to-end traffic is attained. They are adjusted according to the
constraints to obtain the final prediction. Simulation results show that the proposed prediction
approach can accurately predict end-to-end traffic and capture its dynamic change, and in contrast
to previous methods, it holds the better prediction