Provisioning on-line games: a traffic analysis of a busy counter-strike server

This paper describes the results of a 500 million packet trace of a popular on-line, multi-player, game server. The results show that the traffic behavior of this heavily loaded game server is highly predictable and can be attributed to the fact that current game designs target the saturation of the narrowest, last-mile link. Specifically, in order to maximize the interactivity of the game and to provide relatively uniform experiences between all players, on-line games typically fix their usage requirements in such a way as to saturate the network link of their lowest speed players. While the traffic observed is highly predictable, the trace also indicates that these on-line games provide significant challenges to current network infrastructure. Due to synchronous game logic requiring an extreme amount of interactivity, a close look at the trace reveals the presence of large, highly periodic, bursts of small packets. With such stringent demands on interactivity, routers must be designed with enough capadty to quickly route such bursts without delay. As current routers are designed for bulk data transfers with larger packets, a significant, concentrated deployment of online game servers will have the potential for overwhelming current networking equipment.

[1]  Tristan Henderson.  Observations on game server discovery mechanisms , 2002, NetGames '02.

[2]  Jonathan Walpole,et al.  Supporting low latency TCP-based media streams , 2002, IEEE 2002 Tenth IEEE International Workshop on Quality of Service (Cat. No.02EX564).

[3]  Tristan Henderson,et al.  Latency and User Behaviour on a Multiplayer Game Server , 2001, Networked Group Communication.

[4]  Saleem N. Bhatti,et al.  Modelling user behaviour in networked games , 2001, MULTIMEDIA '01.

[5]  Anja Feldmann,et al.  Measurement and analysis of IP network usage and behavior , 2000, IEEE Commun. Mag..

[6]  Andras Veres,et al.  The chaotic nature of TCP congestion control , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[7]  Michael S. Borella,et al.  Source models of network game traffic , 2000, Comput. Commun..

[8]  K. Claffy,et al.  Trends in wide area IP traffic patterns - A view from Ames Internet Exchange , 2000 .

[9]  FeldmannA.,et al.  Data networks as cascades , 1998 .

[10]  Anja Feldmann,et al.  Data networks as cascades: investigating the multifractal nature of Internet WAN traffic , 1998, SIGCOMM '98.

[11]  Paul Barford,et al.  Generating representative Web workloads for network and server performance evaluation , 1998, SIGMETRICS '98/PERFORMANCE '98.

[12]  David Waitzman,et al.  A 50-Gb/s IP router , 1998, TNET.

[13]  Vern Paxson,et al.  End-to-end Internet packet dynamics , 1997, SIGCOMM '97.

[14]  Bruce A. Mah,et al.  An empirical model of HTTP network traffic , 1997, Proceedings of INFOCOM '97.

[15]  Azer Bestavros,et al.  Self-similarity in World Wide Web traffic: evidence and possible causes , 1996, SIGMETRICS '96.

[16]  V. Paxson,et al.  Wide-area traffic: the failure of Poisson modeling , 1994, SIGCOMM.

[17]  Vern Paxson,et al.  Empirically derived analytic models of wide-area TCP connections , 1994, TNET.

[18]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[19]  I. Scott MacKenzie,et al.  Lag as a determinant of human performance in interactive systems , 1993, INTERCHI.

[20]  Henry Fuchs,et al.  On visible surface generation by a priori tree structures , 1980, SIGGRAPH '80.

[21]  H. E. Hurst,et al.  Long-Term Storage Capacity of Reservoirs , 1951 .