摘要
互联网测量的研究促进了路由器级拓扑发现的发展,而网络层的子网能为其提供更详细的中间互补视图.针对子网边界条件以及完整性考虑不足引起的准确率较低问题,提出了一种多特征结合子网发现算法.研究了同一子网IP的traceroute路径特征,将多个特征结合设计更精准的子网边界判定条件.通过筛选子网的完整性,缩小候选子网的搜索空间,启发式求解子网发现问题.实验结果表明,本文算法与现有其他算法相比,能更准确地发现子网,有效地减少子网误报情况,同时效率有所提高.最后,对六个地理上分散的ISP进行子网推断,并分析了这些ISP之间常见的各种子网特征.
The studies on internet measurement have facilitated the development of router-level topology discovery,while subnets in the network layer provide a more detailed intermediate complementary view.In order to deal with the low accuracy caused by insufficient subnet boundary conditions and completeness,a multi-characteristic subnet discovery algorithm was proposed.The characteristics of the traceroute path of IP in the same subnet were studied,and were then combined to generate more precise subnet boundary determination conditions.By filtering the completeness of a subnet,the search space of the candidate subnet was narrowed,and the problem of subnet discovery was solved iteratively.The experimental results show that the proposed algorithm can discover subnets more accurately than other existing algorithms,reduce false positive rate,and improve efficiency.Finally,subnets were inferred on six geographically disperse ISPs,and the common subnet characteristics appearing in these ISPs are analyzed.
作者
姚巍
赵海
朱剑
陈香伊
YAO Wei;ZHAO Hai;ZHU Jian;CHEN Xiang-yi(School of Computer Science&Engineering,Northeastern University,Shenyang 110169,China)
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2020年第8期1075-1082,共8页
Journal of Northeastern University(Natural Science)
基金
中央高校基本科研业务费专项资金资助项目(2020GFZD014,N180716019)
国家重点研发计划项目(2019JSJ12ZDYF01).
