摘要
针对RFC算法随着规则集规模的增加,占用的内存空间以近似指数规模骤然增大的问题,提出了一种改进型的包分类算法HRFC(Hybrid-RFC)。该算法通过决策树完成规则集多维空间的动态划分,借助多阶段缩减树完成对每个子集的映射,从而实现包的快速高效分类。实验表明,该算法能够在保障分类速度的同时,有效地降低空间开销。
According to the existing problem that memory usage grows exponentially with the size increase of rule set in RFC （recursive flow classification） algorithm, an improved packet classification algorithm, HRFC （Hy- brid-RFC） was put forward. The new algorithm completes the dynamic division of a multidimensional space rule set by a decision tree, accomplishes the mapping of each subset with multiple phase reduction trees, so as to realize fast and efficient packet classification. The simulation results show that the new algorithm can reduce the space usage effectively while guaranteeing the performance of classification speed.
作者
陈小雨
陆月明
CHEN Xiaoyu1＇2, LU Yueming1＇2(1.School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China 2. Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing 100876, Chin)
出处
《网络与信息安全学报》
2018年第3期35-41,共7页
Chinese Journal of Network and Information Security
基金
国家重点研究计划基金资助项目(No.2016YFB0800302)~~
关键词
RFC
包分类
决策树
划分
RFC, packet classification, decision tree, division
