期刊文献+

基于节点连接度的P2P流量快速识别方法 被引量:3

Rapid P2P Traffic Identification Method Based on Node Link Degree
下载PDF
导出
摘要 为实现快速有效的P2P流量识别,提出一种基于节点连接度的识别方法。根据不同P2P流量的连接度特点,通过实验分析得到相关的流量属性,对属性进行关联,由此区分网络中的P2P流量及非P2P流量,并通过分析P2P下载与P2P流媒体的行为特性,证明P2P下载的流量属性具有相似性,与P2P流媒体的流量属性相差较大。仿真实验结果证明,该方法具有较好的实时性和准确性。 This paper proposes an identification method which can achieve traffic identification with great efficiency and speed based on connectivity degree of nodes. P2P traffic is distinguished from non-P2P traffic in network by associating the attributes of the two kinds of traffic which are obtained by analyzing the experimental results according to connectivity degree features of different P2P traffic. The facts that traffic attributes of P2P downloading are similar and traffic attributes of P2P downloading are different from traffic attributes of P2P streaming media are proved by analyzing the behavioral properties of P2P downloading and P2P streaming media. Experimental results show that the proposed method has good performance in instantaneity and accuracy.
出处 《计算机工程》 CAS CSCD 2012年第21期119-122,共4页 Computer Engineering
基金 国家自然科学基金资助项目(60902021 60932005 61171109)
关键词 P2P网络 连接度 度分布 复杂网络 流量识别 流量属性 P2P network link degree degree distribution complex network traffic identification traffic attribute
  • 相关文献

参考文献7

  • 1袁雪美,王晖,张鑫,刘亚杰.P2P流量识别技术综述[J].计算机应用,2009,29(B12):11-15. 被引量:10
  • 2Zhu Ke, Hu Hongchao, Yi Peng. Identifying P2P Flow with Behavior Characteristic[C]//Proc. of the 2nd International Conference on Future Computer and Communication. Wuhan, China: [s. n.], 2010.
  • 3Chen Yu, Ping Xiayu, Wei Tao. Application Traffic Classification Based on Command Exchange Mode of TCP Flows[C]//Proc. of IEEE International Conference on Information Theory and Information Security. Beijing, China: [s. n.], 2010.
  • 4谭骏,陈兴蜀,杜敏.基于特征加权与最近邻法的P2P协议识别算法[J].四川大学学报(工程科学版),2011,43(4):116-123. 被引量:1
  • 5Ye Lin, Zhang Hongli, Dai Qiang. Identifying P2P Application with DHT Behaviors[J]. Information Technology Journal, 2011, 10(3): 565-572.
  • 6杨岳湘,王锐,唐川,李强.基于双重特征的P2P流量检测方法[J].通信学报,2006,27(z1):134-139. 被引量:8
  • 7Iliofotou M, Kim H C, Faloutsos M. Graption: A Graph-based P2P Traffic Classification Framework for the Intemet Backbone[J]. Computer Networks, 2011, 55(8): 2-5.

二级参考文献66

  • 1杨岳湘,王锐,唐川,李强.基于双重特征的P2P流量检测方法[J].通信学报,2006,27(z1):134-139. 被引量:8
  • 2陈亮,龚俭,徐选.基于特征串的应用层协议识别[J].计算机工程与应用,2006,42(24):16-19. 被引量:43
  • 3石萍,陈贞翔,荆山,贾冠昕,杨波.基于对等特征的P2P流量识别方法[J].中国教育网络,2007(2):36-38. 被引量:9
  • 4KIM M S, KANG H J, HONG J W. Towards peer-to-peer traffic a-, nalysis using flows[ C]//Self-Managing Distributed Systems, LNCS 2867. Berlin: Springer, 2004:55 - 67.
  • 5OHZAHATA S, HAGIWARAL Y, TERADAL M. A traffic identification method and evaluations for a pure P2P application[ C]//Passive and Active Measurement, LNCS 3431. Heidelberg: Springer- Verlag, 2005:55 -68.
  • 6WANG J S, HANG Y, WU Q. Connection pattern-based P2P application identification characteristic[ C]//Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops. Washington, DC: IEEE Computer Society, 2007:437 -441.
  • 7LU X, DUAN H X, LI X. Identification of P2P traffic based on the content redistribution characteristic[ C]// Communications and Information Technologies. Washington, DC: IEEE Computer Society, 2007:596-601.
  • 8CONSTANTINOU F, MAVROMMATIS P. Identifying known and unknown peer-to-peer traffic[ C]// The 15th IEEE International Symposium on Network Computing and Applications. Washington, DC: IEEE Computer Society, 2006:93 - 102.
  • 9KARAGIANNIS T, BROIDO A, FALOUYSOS M. Transport layer identification of P2P traffic[ C]// Proceedings of the 4th ACM SIGCOMM Conference on Internet Measurement. New York: ACM, 2004:121 - 134.
  • 10KARAGIANNIS T, PAPAGIANNAKI K, FALOUTSOS M. Blinc: multilevel traffic classification in the dark[ J]. ACM SIGCOMM Comprter Communication Review, 2005,35(4): 229-240.

共引文献16

同被引文献26

  • 1VALENTI S, ROSSI D, MEO M,et al. Accurate, fine- grained classification of P2P-TV applications by simply counting packets[C].First International Workshop on Traffic Monitoring and Analysis, Aachen, Germany, 2009.
  • 2万成威.基于P2P流媒体模型的流量特征分析及实时分类[D].郑州:解放军信息工程大学,2012.
  • 3KARAGIANNIS T, PAPAGIANNAKI K, FALOUTSOS M. BLINC: multilevel traffic classification in the dark[C].ACM SIGCOMM Conference, Philadelphia, USA, 2005.
  • 4Ciullo D, Garcia M A, Horvath A, et al. Network awareness of P2P live streaming applications: a measurement study [ J ] IEEE Transactions on Multimedia, 2010, 12( 1 ).. 54-63.
  • 5Valenti S, Rossi D, Meo M,et al. Accurate, fine-gralned classification of P2P-TV applications by simply counting packets [ C ]//First International Workshop on Traffic Monitoring and Analysis. 2009: 84-92.
  • 6Karagiannis T, Papagiannaki K, Faloutsos M. BLINC: multilevel traffic classification In the dark[ C ]//ACM SIGCOMM Con- ference. 2005 : 229-240.
  • 7Zhu Ke, Hu Hongchao, Yi Peng. Identifying P2P Flow with Behavior Characteristic[ C]//Proc. of the 2nd International Con- ference on Future Computer and Communication. 2010:26-29.
  • 8鲁刚,张宏莉,叶麟.P2P流量识别[J].软件学报,2011,22(6):1281-1298. 被引量:48
  • 9胡超,陈鸣,许博,李兵.实时识别P2P-TV视频流的方法研究[J].电子与信息学报,2011,33(9):2219-2224. 被引量:2
  • 10阳旺,李贺武,吴茜,吴建平.互联网端到端多径可靠传输协议研究[J].计算机研究与发展,2012,49(2):261-269. 被引量:8

引证文献3

二级引证文献4

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部