基于随机图的复杂网络建模方法研究  

Maximum Scatter Difference Uncorrelated Based on Locality Preserving Projections

作　　者：李姝 邵志香 于金刚[4] LI Shu;SHAO Zhi-xiang;YU Jin-gang(School of Institute of Equipment Engineering,Shenyang Ligong University,Shenyang 110159,China;State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Effective Development,Beijing 100101,China;Sinopec Research Institute of Petroleum Engineering,Beijing 100101,China;Shenyang Institute of Computing Technology,Chinese Academy of Sciences,Shenyang 110168,China)

机构地区：[1]沈阳理工大学装备工程学院,沈阳110159 [2]页岩油气富集机理与有效开发国家重点实验室,北京100101 [3]中国石化石油工程技术研究院,北京100101 [4]中国科学院沈阳计算技术研究所,沈阳110168

出　　处：《小型微型计算机系统》2020年第9期1935-1938,共4页Journal of Chinese Computer Systems

基　　金：辽宁省“百千万人才工程”项目(2019-45-12)资助。

摘　　要：随着Internet技术的飞速发展,网络传输中大容量、高速化、多媒体化的需求也在日益增长,网络服务性能一直以来是网络传输中备受关注的问题,因此建立一个接近于实际通信网络的复杂网络仿真模型,对深入研究其网络连接状况及网络性能,拓展复杂网络理论研究基础和应用领域,具有十分重要的意义.本文在随机图理论的基础上,提出了一种基于随机图的k-叉树网络模型(k-Tree Network Model based on Random-Graph,k-RGN),该网络仿真模型是一种具有链路权重且服从指数分布的随机网络模型.通过在网络仿真模型中的对比实验,验证了k-RGN随机网络模型,在带宽、丢包率、时延、时延抖动、跳数等多参数指标规划中,具有很好的网络综合性能.With the rapid development of Internet technology,the demand for large-capacity,high-speed,and multimedia of the network transmission is also increasing.The performance of network service has always been a concern in network transmission.Establishing a complex network simulation model which is Approximated to the actual communication network,is of great significance to further study the performance of the network service and expand the theoretical research foundation and application field of complex network.On the basis of random graph theory,a k-Tree Network Model based on Random-Graph(k-RGN)is proposed.It is a network simulation model with links A random network model with weights and exponential distribution.Through the comparative experiments in the network simulation model,it is verified that the k-RGN random network model has good network comprehensive performance in the multi parameter planning of bandwidth,packet loss rate,delay,delay jitter,hop number and so on.

关 键 词：随机图理论 k-叉树 网络性能分析 网络建模 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]