网络业务流的自相似性对网络性能的影响

Effect of Traffic Self-Similarity on Network Performance

传统马尔可夫排队模型的结果与实际的性能有很大的差异 ,其原因在于网络传输过程中存在自相似性 ,突发可能在所有时间级别发生 ,它所需的缓冲容量远远大于泊松分布到达的缓冲容量。揭示了网络自相似性的特性 ,分析了产生自相似性的原因 ,以及它对网络性能的影响 ,并给出了使用概率统计的方法 ,可以达到预测处理到达的业务流 ,提高网络的利用效率。

The results of rtaditional Markovian traffic model differ greatly with actual traffic in network performance. The reason is that there is self similarity in network communication. Bursts can happen in any range of thime. Its buffer requirement is far greater than that of Poisson distribution. This paper reveals features and underlying cause of self similarity traffic, investigates the effect of self similarity traffic on network performance, and presents an approach to predict traffic with probability to improve the network utilization rate.