基于空时分形的网络流量认知模型
Network traffic cognition model based on space-time fractals
摘要
Abstract
Considering the problem of traditional fractal(TF)features being difficult to achieve both high accuracy and fast speed in network traffic cognition,the idea of space-time separation was proposed on the basis of fractal theory.With space-time fractal(SF)features generated by the space-time separation,a new traffic cognition system called the space-time fractal model(SFM)was established.In order to obtain SF,the spatial and temporal sequences were ob-served,and further constructed to generate vectors by Legendre transformation,which were mapped into dual space.The physical significance of SF lied in capturing the characteristics of traffic bursts at different scales of space and time,while TF were the fusion of SF across spatial and temporal scales.Compared with TF,SF represented network traffic more comprehensively and thus were able to identify traffic more accurately.Moreover,SF were more computationally efficient than TF,enabling SFM to achieve high cognition speed as well as strong cognition accuracy.The experimental results show that the cognition performance of SFM is superior to other methods.关键词
网络流量/认知精度/认知速度/分形理论Key words
network traffic/cognition accuracy/cognition speed/fractal theory分类
信息技术与安全科学引用本文复制引用
汤萍萍,张晖,董育宁,董国青..基于空时分形的网络流量认知模型[J].通信学报,2025,46(5):258-271,14.基金项目
国家自然科学基金资助项目(No.62071005) （No.62071005）
国家重点研发计划基金资助项目(No.2020YFB2104004) （No.2020YFB2104004）
江苏省重点研发计划基金资助项目(No.BE2021725) （No.BE2021725）
安徽省自然科学基金资助项目(No.2308085Y02,No.2208085MF155) （No.2308085Y02,No.2208085MF155）
安徽省高校自然科学基金资助项目(No.KJ2021A0124) （No.KJ2021A0124）
安徽省博士后科研基金资助项目(No.2024C946)The National Natural Science Foundation of China(No.62071005),The National Key Research and Develop-ment Program of China(No.2020YFB2104004),The Key Research and Development Program of Jiangsu Province(No.BE2021725),The Natural Science Foundation of Anhui Province(No.2308085Y02,No.2208085MF155),The Natural Science Foundation of the Higher Education Institutions of Anhui Province(No.KJ2021A0124),The Anhui Postdoctoral Scientific Research Program Founda-tion(No.2024C946) （No.2024C946）
