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Server Allocation for Massively Multiplayer Online Cloud Games Using Evolutionary Optimization

机译:使用进化优化的大型多人在线云游戏服务器分配

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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.
机译:近年来,大规模的多人游戏在线游戏(MMOG)正在变得流行,部分由于他们复杂的图形和广泛的虚拟世界,而且云游戏的要求比以往任何时候都在娱乐和便携式设备上娱乐时都是如此。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。该问题的配合为最小化涉及服务器租赁成本,数据传输成本和游戏时间的网络延迟的目标函数。开发了一种遗传算法,解决了用于处理登录系统的玩家的同时服务器的最小化问题,同时许多现有玩家正在播放同一游戏。基于“魔兽世界”在“魔兽世界”中的广泛实验是进行的,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,该方法在大部分时间内给出了较低的成本和更短的网络延迟。

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