Adaptive Server Selection for Large Scale Interactive Online Games

In this paper, we present a novel distributed algorithm that dynamically selects game servers for a group of game clients participating in large scale interactive online games. The goal of server selection is to minimize server resource usage while satisfying the real-time delay constraint. We develop a synchronization delay model for interactive games and formulate the server selection problem, and prove that the considered problem is NPhard. The proposed algorithm, called the zoom-in-zoom-out, is adaptive to session dynamics (e.g. clients join and leave) and lets the clients to select appropriate servers in a distributed manner such that the number of servers used by the game session is minimized. Using simulation, we present the performance of the proposed algorithm and show that it is simple yet effective in achieving its design goal. In particular, we show that the performance of our algorithm is comparable to that of a greedy selection algorithm, which requires global information and excessive computation.

By: Kang-Won Lee, Seraphin B. Calo, Bong-Ju Ko

Published in: Computer Networks, volume 49, (no 1), pages 84-102 in 2005

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