In recent years, Massively Multiplayer Online Games (MMOGs) are becoming popular, partially due to their sophisticated graphics and broad virtual world, and cloud gaming is demanded more than ever especially when entertaining with light and portable devices. This article considers the problem of server allocation for running MMOG on cloud, aiming to reduce the cost on cloud gaming service and meanwhile enhance the quality of service. The problem is formulated into minimizing an objective function involving the cost of server rental, the cost of data transfer and the network latency during the gaming time. A genetic algorithm is developed to solve the minimization problem for processing simultaneous server allocation for the players who log into the system at the same time while many existing players are playing the same game. Extensive experiments based on the player behavior in “World of Warcraft” are conducted to evaluate the proposed method and compare with the state-of-the-art as well. The experimental results show that the method gives a lower cost and a shorter network latency in most of the time.

中文翻译：

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使用进化优化的大型多人在线云游戏的服务器分配

近年来，大型多人在线游戏 (MMOG) 变得流行，部分原因在于其复杂的图形和广阔的虚拟世界，云游戏的需求比以往任何时候都高，尤其是在使用轻便和便携式设备进行娱乐时。本文考虑了在云上运行MMOG的服务器分配问题，旨在降低云游戏服务的成本，同时提高服务质量。该问题被表述为最小化涉及服务器租赁成本、数据传输成本和游戏期间网络延迟的目标函数。开发了一种遗传算法来解决同时登录系统的玩家同时进行服务器分配的最小化问题，同时许多现有玩家正在玩同一个游戏。基于“魔兽世界”中玩家行为的广泛实验，以评估所提出的方法并与最先进的方法进行比较。实验结果表明，该方法在大多数情况下提供了较低的成本和较短的网络延迟。