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File-aware P2P traffic classification: An aid to network management

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Abstract

As P2P dominates Internet traffic in recent years, ISPs are striving to balance between providing the basic networking services for P2P users and properly managing network bandwidth usage. That is, ISPs are required to provide proper bandwidth for each P2P user to get every file to fulfill their provision for communications, while they have to control bandwidth consumption for efficient usage. However, current P2P traffic management strategies are unable to satisfy both requirements. In this paper, our goal is to design a simple and effective scheme for ISPs to moderate the tradeoff. It is achieved by proposing a file-aware P2P traffic classification method that can identify files and the associated flows. The file-level information can lead to more efficient and flexible management strategies on a per-file basis. We offer two alternatives: constraining the per-file bandwidth consumption and the number of per-file concurrent flows. Finally, a real-life trace is measured using our file-aware method from the perspectives of peers and files. The results indicate that ISPs can gain enough opportunities to flexibly choose proper traffic manage parameters according to actual demands.

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References

  1. Aceto G, Dainotti A, de Donato W, Pescape A (2010) PortLoad: taking the best of two worlds in traffic classification. In: Proc. INFOCOM workshops, San Diego, CA, USA

  2. BlueCoat (2011) Blue coat packetShaper. http://www.bluecoat.com/products/packetshaper. Accessed 3 Sep 2011

  3. Canini M, Li W, Moore A, Bolla R (2009) GTVS: boosting the collection of application traffic ground truth. In: Proc. 1st international workshop on traffic monitoring and analysis, Aachen, Germany

  4. Cisco (2005) Managing Peer-to-Peer traffic with cisco service control technology. http://www.cisco.com/en/US/prod/collateral/ps7045/ps6129/ps6133/ps6150/prod_white_paper0900aecd8023500d.html. Accessed 3 Sep 2011

  5. Cohen B (2004) The bitTorrent protocol specification. http://www.bittorrent.org/beps/bep_0003.html. Accessed 3 Sep 2011

  6. Dischinger M, Marcon M, Guha S, Gummadi K, Mahajan R, Saroiu S (2010) Glasnost: enabling end users to detect traffic differentiation. In: Proc. USENIX NSDI, San Jose, California, USA

  7. Erman J, Mahanti A, Arlitt M (2007a) Byte me: a case for byte accuracy in traffic classification. In: Proc. SIGCOMM MineNet workshop, San Diego, CA, USA

  8. Erman J, Mahanti A, Arlitt M, Williamson C (2007b) Identifying and discriminating between web and Peer-to-Peer traffic in the network core. In: Proc. ACM WWW, Banff, Alberta, Canada

  9. F5 (2007) Bandwidth management for Peer-to-Peer applications. http://www.f5.com/pdf/white-papers/rateshaping-wp.pdf. Accessed 3 Sep 2011

  10. Gallagher B, Iliofotou M, Eliassi-Rad T, Faloutsos M (2010) Link homophily in the application layer and its usage in traffic classification. In: Proc. IEEE INFOCOM, San Diego, CA, USA

  11. Haffner P, Sen S, Spatscheck O, Wang D (2005) ACAS: automated construction of application signatures. In: Proc. SIGCOMM MineNet workshops, Philadelphia, PA, USA

  12. Iliofotou M, Faloutsos M, Mitzenmacher M (2009) Exploiting dynamicity in graph-based traffic analysis: techniques and applications. In: Proc. ACM CoNEXT, Rome, Italy

  13. Karagiannis T, Papagiannaki K, Faloutsos M (2005) BLINC: multilevel traffic classification in the dark. In: Proc. ACM SIGCOMM, Philadelphia, PA, USA

  14. Kim H, Claffy K, Fomenkov M, Barman D, Faloutsos M, Lee K (2008) Internet traffic classification demystified: myths, caveats, and the best practices. In: Proc. ACM CoNEXT, Madrid, Spain

  15. Kulbak Y, Bickson D (2005) The eMule protocol specification. http://www.cs.huji.ac.il/labs/danss/p2p/resources/emule.pdf. Accessed 3 Sep 2011

  16. Kumar S, Turner J, Crowley P (2008) Peacock hashing: deterministic and updatable hashing for high performance networking. In: Proc. IEEE INFOCOM, Phoenix, AZ, USA

  17. LimeWire (2008) Gnutella protocol specification. http://wiki.limewire.org/index.php?title=GDF. Accessed 3 Sep 2011

  18. Ma J, Levchenko K, Kreibich C, Savage S, Voelker G (2006) Unexpected means of protocol inference. In: Proc. SIGCOMM IMC, Rio de Janeiro, Brazil

  19. Mohammadi M, Raahemi B, Akbari A, Moeinzadeh H, Nasersharif B (2011) Genetic-based minimum classification error mapping for accurate identifying Peer-to-Peer applications in the internet traffic. Expert Syst Appl 38(6):6417–6423

    Article  Google Scholar 

  20. Moore A, Papagiannaki K (2005) Toward the accurate identification of network applications. In: Proc. passive and active network measurement, Boston, USA

  21. Nam G, Patankar P, Kesidis G, Das C, Seren C (2009) Mass purging of stale tcp flows in per-flow monitoring systems. In: Proc. IEEE ICCCN, San Franciso, CA, USA

  22. Nguyen T, Armitage G (2008) A survey of techniques for internet traffic classification using machine learning. IEEE Commun Surv Tutor 10(4):56–76

    Article  Google Scholar 

  23. Qi Y, Xu B, He F, Yang B, Yu J, Li J (2007) Towards high-performance flow-level packet processing on multi-core network processors. In: Proc. ACM ANCS, Orlando, Florida, USA

  24. Raahemi B, Mumtaz A (2010) Classification of Peer-to-Peer traffic using a two-stage window-based classifier with fast decision tree and ip layer attributes. International Journal of Data Warehousing and Mining (IJDWM) 6(3):28–42

    Article  Google Scholar 

  25. Raahemi B, Hayajneh A, Rabinovitch P (2007) Peer-to-Peer ip traffic classification using decision tree and ip layer attributes. International Journal of Business Data Communications and Networking (IJBDCN) 3(4):60–74

    Article  Google Scholar 

  26. Raahemi B, Zhong W, Liu J (2009) Exploiting unlabeled data to improve Peer-to-Peer traffic classification using incremental tri-training method. Peer-to-Peer Netw Appl 2(2):87–97

    Article  Google Scholar 

  27. Ramakrishna M, Fu E, Bahcekapili E (1994) A performance study of hashing functions for hardware applications. In: Proc. ICCI, Peterborough, Ontario, Canada

  28. Sandvine (2008) Sandvine white paper. http://www.sandvine.com. Accessed 3 Sep 2011

  29. Schulze H, Mochalski K (2010) Internet study 2008/2009. http://www.ipoque.com/resources/internet-studies/internet-study-2008_2009. Accessed 3 Sep 2011

  30. Sen S, Spatscheck O, Wang D (2004) Accurate, scalable in-network identification of P2P traffic using application signatures. In: Proc. ACM WWW, New York, USA

  31. Song H, Dharmapurikar S, Turner J, Lockwood J (2005) Fast hash table lookup using extended bloom filter: an aid to network processing. In: Proc. ACM SIGCOMM, Philadelphia, PA, USA

  32. Xu J, Singhal M (2002) Cost-effective flow table designs for high-speed routers: architecture and performance evaluation. IEEE Trans Comput 51(9):1089–1099

    Google Scholar 

  33. Ye M, Wu J, Xu K, Chiu D (2009) Identify P2P traffic by inspecting data transfer behaviour. In: Proc. IFIP NETWORKING, Aachen, Germany

  34. Zhou Z, Song T (2011) File-aware P2P traffic classification. In: Proc. IEEE GLOBECOM workshops, Houston, Texas, USA

  35. Zhou Z, Song T, Wenliang F (2012) RocketTC: a high throughput traffic classification architecture. In: Proc. IEEE ICNC, Maui, Hawaii, USA

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (Grant No. 61272510, 60803002), Beijing Key Discipline Program. We thank Dr. Zhaoyi Wei for his help and valuable suggestions. Thanks also to the editors and reviewers for their insightful comments.

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Correspondence to Tian Song.

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Song, T., Zhou, Z. File-aware P2P traffic classification: An aid to network management. Peer-to-Peer Netw. Appl. 6, 325–339 (2013). https://doi.org/10.1007/s12083-012-0172-4

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