一种改进的高速网络分布式流量抽样算法

doi:10.3969/j.issn.1001-2400.2013.03.024

J4 ›› 2013, Vol. 40 ›› Issue (3): 160-165.doi: 10.3969/j.issn.1001-2400.2013.03.024

一种改进的高速网络分布式流量抽样算法

孙昱¹;蒋馥蔚¹;夏靖波¹;赵小欢¹;申健¹;李明辉²

(1. 空军工程大学信息与导航学院，陕西西安 710077；
2. 空军后勤部，北京 100720)

收稿日期:2012-09-27 出版日期:2013-06-20 发布日期:2013-07-29
作者简介:孙昱(1989-)，男，空军工程大学博士研究生，E-mail: 458657673@qq.com．
基金资助:
陕西省科技计划资助项目(2012JZ8005);全军军事学研究生课题资助项目(2010XXXX-488)

Improved distributed traffic sampling algorithm for high speed network

SUN Yu¹;JIANG Fuwei¹;XIA Jingbo¹;ZHAO Xiaohuan¹;SHEN Jian¹;LI Minghui²

(1. School of Information and Navigation, Air Force Engineering Univ., Xi'an 710077， China;
2. Air Force Logistics Department, Beijing 100720， China)

Received:2012-09-27 Online:2013-06-20 Published:2013-07-29

摘要/Abstract

摘要：

针对基于掩码匹配的抽样算法中使用某些抽样掩码会造成较大测量误差的问题，提出了一种增强样本随机性的改进方案．该方案首先对标识字段进行异或运算，以得到新的标识值；然后再进行匹配抽样．从理论上证明了异或运算能有效提高结果的随机性，并用实测流量数据进行了统计验证．最后，从有效性和稳定性两个方面对改进算法进行了检验．实验结果表明，改进算法的各项评价指标均优于文献［10］算法，任意的抽样掩码均能在改进算法中使用．

关键词: 分布式抽样, 掩码匹配, 标识字段, 随机性, 异或运算

Abstract:

The sampling algorithm based on mask matching is a distributed sampling measurement technology which can be used in a high speed network. But there exists a problem that some masks used in the algorithm result in a large measurement error. In order to solve the problem, the paper proposes an improved scheme that aims to enhance the randomness of its sample. The idea of the scheme is to put the identification field into xor operation to get a new identity value before mask matching and sampling. Firstly, the paper demonstrates theoretically that the xor operation can enhance its computed result's randomness effectively. Then it is checked statistically with the realistic traffic data. Finally, the improved algorithm is tested from two aspects of effectiveness and stability. Experimental result shows that the evaluation indexes of the improved algorithm are better than those of the original algorithm. Hence, any sampling mask can be used in the improved algorithm.

Key words: distributed sampling, mask matching, identification field, randomness, xor operation

孙昱;蒋馥蔚;夏靖波;赵小欢;申健;李明辉. 一种改进的高速网络分布式流量抽样算法[J]. J4, 2013, 40(3): 160-165.

SUN Yu;JIANG Fuwei;XIA Jingbo;ZHAO Xiaohuan;SHEN Jian;LI Minghui. Improved distributed traffic sampling algorithm for high speed network[J]. J4, 2013, 40(3): 160-165.

参考文献

［1］ Claffy K C, Polyzos G C, Braun H W. Application of Sampling Methodologies to Network Traffic Characterization ［J］. SIGCOMM Computer Communication Review,1993, 23(4): 194-203.
［2］陈松, 王珊, 周明天. 基于实时分析的网络测量抽样统计模型［J］. 电子学报, 2010, 38(5): 1177-1180.
Chen Song, Wang Shan, Zhou Mingtian. Network Data Measurement and Statistics Model Based on Real-time Analysis ［J］. Acta Electronica Sinica, 2010, 38(5): 1177-1180.
［3］潘乔, 罗辛, 王高丽, 等. 基于FARIMA模型的流量抽样测量方法［J］. 计算机工程, 2010, 36(15): 7-11.
Pan Qiao, Luo Xin, Wang Gaoli, et al. Traffic Sampling Measurement Method Based on FARIMA Model ［J］. Computer Engineering, 2010, 36(15): 7-11.
［4］陈庶樵, 张果, 朱柯. 一种基于包速率自适应的报文抽样算法［J］. 计算机应用研究, 2010, 27(7): 2727-2729.
Chen Shuqiao, Zhang Guo, Zhu Ke. Algorithm Based on Packet Rate Adaptive for Packet Sampling ［J］. Application Research of Computers, 2010, 27(7): 2727-2729.
［5］ Cozzani I, Giordano S. A Passive Test and Measurement System: Traffic Sampling for QoS Evaluation ［C］//Proceedings of GLOBECOM 1998. Sydney: IEEE, 1998: 1236-1241.
［6］ Duffield N, Grossglauser M. Trajectory Sampling for Direct Traffic Observation ［J］. IEEE/ACM Trans on Networking, 2001, 9(3): 280-292.
［7］ Duffield N, Lund C, Thorup M. Learn More, Sample Less: Control of Volume and Variance in Network Measurement ［J］. IEEE Trans on Information Theory, 2005, 5(51): 1756-1775.
［8］潘乔, 裴昌幸. 用于高速IPv6网络流量抽样测量的算法［J］. 西安电子科技大学学报, 2007, 34(3): 377-381.
Pan Qiao, Pei Changxing. Method for Traffic Sampling in High-speed IPv6 Networks ［J］. Journal of Xidian University, 2007, 34(3): 377-381.
［9］潘乔, 裴昌幸. 基于信息熵理论的高速IPv6网络流量抽样测量方法［J］. 吉林大学学报(工学版), 2009, 39(5): 1338-1341.
Pan Qiao, Pei Changxing. Information Entropy Theoretic Approach to Traffic Sampling Measurement in High-speed IPv6 Networks ［J］. Journal of Jilin University(Engineering and Technology Edition), 2009, 39(5): 1338-1341.
［10］程光, 龚俭, 丁伟. 基于统计分析的高速网络分布式抽样测量模型［J］. 计算机学报, 2003, 26(10): 1266-1273.
Cheng Guang, Gong Jian, Ding Wei. Distributed Sampling Measurement Model in a High Speed Network Based on Statistical Analysis ［J］. Chinese Journal of Computers, 2003, 26(10): 1266-1273.
［11］王海涛, 吴连才, 武媛媛. 基于掩码匹配的IP网络抽样测量系统的设计和实现［J］. 数据通信, 2011(2): 18-21.
Wang Haitao, Wu Liancai, Wu Yuanyuan. Design and Implementation of a Flow Sampling Measurement System Based on Mask Matching on IP Network ［J］. Data Communications, 2011(2): 18-21.
［12］李志敏, 赵治国, 朱安新, 等. 校园网流量抽样测量系统设计与实现［J］. 网络安全技术与应用, 2011(11): 70-72.
Li Zhimin, Zhao Zhiguo, Zhu Anxin, et al. Design and Implementation of a Flow Sampling Measurement System on Campus Network ［J］. Network Security Technology and Application, 2011(11): 70-72.
［13］ MAWI Working Group Traffic Archive. Traffic Trace Info ［EB/OL］. ［2012-08-20］. http://mawi.wide.ad.jp/mawi.
［14］盛骤, 谢式千, 潘承毅. 概率论与数理统计［M］. 北京: 高等教育出版社, 2008: 199-200.

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一种改进的高速网络分布式流量抽样算法

Improved distributed traffic sampling algorithm for high speed network

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