摘要
微信是现代互联网的主要应用之一,到目前为止有关微信流量特性分析与建模的研究较少.本文以微信流量为研究对象,分析验证微信流量同时具有自相似性和突发性.针对这两种特性进行微信流量建模,采用线性分形稳定噪声模型刻画微信流量特性,完成了模型的参数估算和效果分析.本文的研究成果是后续的网络性能分析、网络流量监管等的基础.
WeChat is one of the main applications of the modern Internet, but there are few studies on the characteristics analysis and modeling of its network traffic. The study takes WeChat traffic as the research object and finds that it has self-similarity and burstiness. In view of these two characteristics, we use the linear fractional stable noise model to characterize WeChat traffic and carry out the parameter estimation and the effect analysis of the model. The research results provide a basis for subsequent network performance analysis and traffic monitoring.
作者
龚莲
谭献海
GONG Lian;TAN Xian-Hai(School of Information Science and Technology,Southwest Jiaotong University,Chengdu 611756,China)
出处
《计算机系统应用》
2021年第10期325-330,共6页
Computer Systems & Applications
基金
国家科技支撑计划(2015B14B01)。
关键词
微信
网络流量
自相似性
突发性
线性分形稳定噪声模型
WeChat
network traffic
self-similarity
burstiness
linear fractional stable noise model
