针对移动IP频繁快速切换产生的问题，分析了已有的单独利用RSVP和区分服务的解决方案的优缺点，提出了一个综合利用两种服务优点的方案：平时用RSVP提供优质服务，频繁而快速切换时，用DiffServ保证不掉线。

It is difficult to give an accurate judgement of whether the traffic model fit the actual traffic. The traditional method is to compare the Hurst parameter, data histogram and autocorrelation function. The method of comparing Hurst parameter cannot give exact results and judgement. The method of comparing data histogram and autocorrelation only gives a qualitative judgement. Based on linear discriminant analysis we proposed a novel arithmetic. Utilizing this arithmetic we analysed some sets of data with large and little differences. We also analysed some sets of data generated by network simulator. The analysis result is accurate. Comparing with traditional method, this arithmetic is useful and can conveniently give an accurate judgement for complex network traffic trace.

判断网络通信量模型与真实数据拟合度的常用方法是Hurst参数比较法、数据直方图比较法和自相关函数比较法。其中Hurst参数法计算结果不准确，不能给出正确判断，而后两者只能主观给出一个定性判断。基于线性鉴别分析原理，给出了一个拟合度判断算法。用该算法分析了不同差别程度的模型仿真数据和大量NS仿真数据，应用效果显著，与常用方法相比，能定量、准确地判断网络通信量模型的拟合度。

It is not a simple and trivial work to set up an appropriate network traffic model. A fractional Alpha model is proposed in this paper and two proofs based on flow and session level, respectively, are given. Based on this model, the lower bound for the residual of the queueing distribution is deduced. Comparing the residual distribution function (RDF) based on our model with it based on other models, we find our formula matches the real RDF better. Based on this formula, we can predict the need for forwarding performance. Then a novel QoS routing algorithm based on this prediction is proposed. Last we demonstrate a simple example to denote how our algorithm can effectively improve the utility of bandwidth and amount of traffic and guarantee QoS.

分析网络通信量的传统方法是使用变尺度函数计算Hurst参数，其计算结果不准确，不能正确判断模型拟合度。文章使用主成分分析计算Hurst参数，判断通信量模型的拟合度，分析同一模型不同参数的差别不明显的数据，结果表明该方法新颖而有效。