To mitigate the network congestion by node failures, a new effectiveness evaluation method was proposed with reference to wavelet transform. In this method, the long-range dependence of actual traffic was depicted at first, and the prediction algorithm of arrival traffic was established with Auto-Regressive and Moving Average (ARMA) model, of which standard deviation between the prediction data and actual data was 6. 89. Then, a simulation was conducted to research the relationship between the effectiveness and other influential factors. The results show that the effectiveness is of positive correlation with average velocity, and negative correlation with buffer size.%针对因节点失效而产生的网络拥塞现象,结合小波变换提出了一种度量节点有效性的方法.首先刻画实际流量的长相关特性,并且利用自回归滑动平均(ARMA)模型建立到达流量的预测算法,其预测数据与实际信息的标准差为6.89.同时通过仿真实验深入研究了有效性与各影响因素之间的关系,结果表明与平均速率成正相关,而与缓冲区成负相关.
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