基于稳态队列长度的网络流量预测算法

Siyu Dong, Hong Zhang
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引用次数: 1

摘要

为了对网络流量进行定量研究,本文提出了一种基于FARIMA模型稳态队列长度的预测算法PQSF。该算法首先利用基于稳态队列长度的乘积解理论推导出节点分组排队情况,然后计算出存在故障节点时流量平均队列长度的数学公式,并结合FARIMA建立预测方法。最后,通过网络仿真对PQSF算法进行了验证。结果表明,该算法具有较好的自适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An prediction algorithm for network traffic based on the queue length of steady state
In order to make quantitative research on network traffic, this paper puts forward a kind of prediction algorithm based on the queue length of steady state for FARIMA model, PQSF. The algorithm firstly uses the theory of product solution based on the queue length of steady state to derive node packet queuing situation, then calculates the mathematical formula of the traffic's average queue length when there are failure nodes, and establishes the prediction method combined with FARIMA. Finally, this paper validates the PQSF algorithm by the network simulation. The results show that the algorithm has comparatively good adaptability.
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