"Optimising Online FPS Game Server Discovery through Clustering Servers by Origin Autonomous System"

Click here for the pdf pre-print of this paper.

(c) ACM, 2008. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not
for redistribution. The definitive version was published in Proceedings of ACM NOSSDAV 2008, Germany, May 2008

Abstract:

This paper describes the use of origin Autonomous System (AS) information to optimise online First Person Shooter (FPS) game server discovery. Online FPS games typically use a client-server model, with thousands of game servers active at any time. Traditional server discovery probes all available servers over multiple minutes in no particular order, creating thousands of short-lived UDP flows. Using Valve's Counterstrike:Source game this paper demonstrates a multi-step process: Sort available game servers by origin AS, probe a subset of servers in each AS, rank each AS in ascending order of estimated round trip time (RTT), then probe all remaining game servers according to the rank of their origin AS. Probing game servers in approximately ascending RTT expedites the identification of playable servers. This new approach may take less than 20% of the time and network traffic of conventional server discovery (without exceeding conventional server discovery time and traffic consumption in the worst case).