期刊论文详细信息
ETRI Journal
Game Traffic Classification Using StatisticalCharacteristics at the Transport Layer
关键词: traffic measurement;    traffic classification;    Game traffic;   
Others  :  1185983
DOI  :  10.4218/etrij.10.0109.0236
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【 摘 要 】

The pervasive game environments have activated explosive growth of the Internet over recent decades. Thus, understanding Internet traffic characteristics and precise classification have become important issues in network management, resource provisioning, and game application development. Naturally, much attention has been given to analyzing and modeling game traffic. Little research, however, has been undertaken on the classification of game traffic. In this paper, we perform an interpretive traffic analysis of popular game applications at the transport layer and propose a new classification method based on a simple decision tree, called an alternative decision tree (ADT), which utilizes the statistical traffic characteristics of game applications. Experimental results show that ADT precisely classifies game traffic from other application traffic types with limited traffic features and a small number of packets, while maintaining low complexity by utilizing a simple decision tree.

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【 参考文献 】
  • [1]K. Jegers and M. Wiberg, "Pervasive Gaming in the Everyday World," IEEE Pervasive Computing, vol. 5, 2006, pp.78-85.
  • [2]S. McCreary and K. Claffy, "Trends in Wide Area IP Traffic Patterns: A View from Ames Internet Exchange," Proc. 13th ITC Specialist Seminar on Measurement and Modeling of IP Traffic, Sept. 2000, pp. 1-11.
  • [3]L. Liang, Z. Sun, and H Cruickshank, "Relative QoS Optimization for Multiparty Online Gaming in DiffServ Networks," IEEE Commun. Mag., vol. 43, May 2005, pp. 75-83.
  • [4]Game genres. http://en.wikipedia.org/wiki/Game_genres.
  • [5]G. Armitage, M. Claypool, and P. Branch, Networking and Online Games: Understanding and Engineering Multiplayer Internet Game, John Wiley and Sons, 2006, pp. 150-173.
  • [6]Game chart. http://www.gamechart.co.kr/.
  • [7]A. Kind et al., "Advanced Network Monitoring Brings Life to the Awareness Plane," IEEE Commun. Mag., vol. 46, Oct. 2008, pp. 140-146.
  • [8]V. Paxson, "Bro: A System for Detecting Network Intruders in Real-Time," Computer Networks, vol. 31, no. 23-24, 1999, pp. 2435-2463.
  • [9]S. Sen, O. Spatscheck, and D. Wang, "Accurate, Scalable In-Network Identification of P2P Traffic Using Application Signatures," Proc. 13th Int. Conf. World Wide Web, 2004, pp. 512-521.
  • [10]M.S. Kim, Y.J. Won, and J.W.K. Hong, "Application-Level Traffic Monitoring and an Analysis on IP Networks," ETRI J., vol. 27, no. 1, 2005, pp. 22-42.
  • [11]J. Erman, M. Arlitt, and A. Mahanti, "Internet Traffic Classification Using Clustering Algorithms," Proc. ACM SIGCOMM Workshop Mining Network Data, 2006, pp. 281-286.
  • [12]T. Karagiannis et al., "Transport Layer Identification of P2P Traffic," Proc. 4th ACM SIGCOMM Conf. Internet Measurement, 2004, pp. 121-134.
  • [13]A. Madhukar and C. Williamson, "A Longitudinal Study of P2P Traffic Classification," Proc.14th IEEE Int. Symp. Modeling, Analysis, and Simulation, Sept. 2006, pp. 179-188.
  • [14]T. Karagiannis, K. Papagiannaki, and M. Faloutsos, "BLINC: Multilevel Traffic Classification in the Dark," Proc. ACM SIGCOMM, Aug. 2005, pp. 229-240.
  • [15]A.W. Moore and D. Zuev, "Internet Traffic Classification Using Bayesian Analysis Techniques," Proc. SIGMETRICS, June 2005, pp. 50-60.
  • [16]A.W. Moore, "Discriminators for Use in Flow-Based Classification," Technical Report, Intel Research, Cambridge, 2005.
  • [17]M.S. Borella, "Source Models of Network Game Traffic," Computer Commun., vol. 23, no. 4, Feb. 2000, pp. 403-410.
  • [18]J. Färber, "Network Game Traffic Modelling," Proc. 1st Workshop Network and System Support for Games, Bruanschweig, Germany, 2002, pp. 53-57.
  • [19]T. Henderson and S. Bhatti, "Modeling User Behaviour in Networked Games," Proc. 9th ACM Int. Conf. Multimedia, 2001, pp. 212-220.
  • [20]T. Lang, P. Branch, and G. Armitage, "A Synthetic Traffic Model for Quake3," Proc. ACM SIGCHI Int. Conf. Advances in Computer Entertainment Technol., Singapore, June 2004.
  • [21]W.C. Feng, F. Chang, and J. Walpole, "A Traffic Characterization of Popular On-line Games," IEEE/ACM Trans. Networking, vol. 13, no. 3, 2005, pp. 488-500.
  • [22]T. Henderson and S. Bhatti, "Networked Games: A QoS-Sensitive Application for QoS-Insensitive Users?" Proc. ACM SIGCOMM Workshop on Revisiting IP QoS: What Have We Learned, Why Do We Care? 2003, pp. 141-147.
  • [23]A. Dainotti, A. Pescapé, and G. Ventre, "A Packet-Level Traffic Model of Starcraft," Proc. HOT-P2P 2nd Int. Workshop Hot Topics in Peer-to-Peer Systems, San Diego, USA, 2005, pp. 33-42.
  • [24]K.T. Chen, P. Huang, and C.L. Lei, "Game Traffic Analysis: An MMORPG Perspective," Computer Networks, vol. 50, no. 16, 2006, pp. 3002-3023.
  • [25]J. Kim et al., "Traffic Characteristics of a Massively Multi-player Online Role Playing Game," Proc. NetGames, Oct. 2005, pp. 1-8.
  • [26]Internet Assigned Numbers Authority (IANA) port number list. http://www.iana.org/assignments/port-numbers.
  • [27]J. But et al., "Evaluating Machine Learning Methods for Online Game Traffic Identification," Proc. 5th ACM SIGCOMM Workshop on Network and System Support for Games, Technical Report 060410C, CAIA, Apr. 2006.
  • [28]D.J. Parish et al., "Using Packet Size Distributions to Identify Real-Time Networked Applications," IEE Commun., vol. 150, Aug. 2003, pp. 221-227.
  • [29]K. Tsutomu et al., "Traffic Identification for Dependable VoIP," NEC Technical J., vol. 1, no. 3, 2006, pp. 17-20.
  • [30]M. Crotti et al., "Traffic Classification through Simple Statistical Fingerprinting," ACM SIGCOMM Computer Commun. Review, vol. 37, no. 1, Jan. 2007, pp. 5-16.
  • [31]N. Williams, S. Zander, and G. Armitage, "A Preliminary Performance Comparison of Five Machine Learning Algorithms for Practical IP Traffic Flow Classification," ACM SIGCOMM Computer Commun. Review, vol. 36, no. 5, Oct. 2006, pp. 5-16.
  • [32]Gundam-Online (GO). http://gundam.netmarble.net/.
  • [33]KartRider. http://kart.nexon.com/.
  • [34]Stracraft. http://www.blizzard.co.kr/starcraft/.
  • [35]Sudden Attack (SA). http://suddenattack.netmarble.net/.
  • [36]World of Warcraft (WoW). http://www.worldofwarcraft.com/.
  • [37]Dungeon and Fighter (D&F). http://df.hangame.com/.
  • [38]Maple Story (M.S). http://maplestory.nexon.net/.
  • [39]Lineage II. http://www.lineage2.co.kr/.
  • [40]L.J. Gleser and D.S. Moore, "The Effect of Dependence on Chi-Squared and Empiric Distribution Tests of Fit," Annals of Statistics, vol. 11, no. 4, 1983, pp. 1100-1108.
  • [41]N. Williams, S. Zander, and G. Armitage, "Evaluating Machine Learning Algorithms for Automated Network Application Identification," Technical Report 060401B, CAIA, Swinburne Univ., Apr. 2006.
  • [42]M. Kantardzic, Data Mining: Concepts, Methods, and Algorithms, Wiley-IEEE Press, 2003.
  • [43]Perl programming language. http://www.perl.org/.
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