Client-side adaptive search optimisation for online game server discovery

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Abstract

This paper describes a client-side, adaptive search technique to reduce both the time taken to discover playable online First Person Shooter (FPS) game servers and the number of network flows created during game server discovery. Online FPS games usually use a client-server model, with thousands of game servers active at any time. Traditional FPS server discovery probes all available servers over multiple minutes in no particular order, creating thousands of short-lived UDP flows. Probing triggers rapid consumption of longer-lived per-flow state memory in NAT devices between a client and the internet. Using server discovery data from Valve's Counterstrike:Source and idSoftware's Wolfenstein Enemy Territory this paper demonstrates that pre-probing a subset of game servers can be used to re-order and optimise the overall probe sequence. Game servers are now probed in approximately ascending latency, expediting the location of playable servers. Discovery of playable servers may now take less than 20% of the time and network traffic of conventional game server discovery. The worst case converges to (without exceeding) the behaviour of conventional game server discovery. © 2008 Springer-Verlag Berlin Heidelberg.

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APA

Armitage, G. (2008). Client-side adaptive search optimisation for online game server discovery. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4982 LNCS, pp. 494–505). https://doi.org/10.1007/978-3-540-79549-0_43

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