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Let's depart together: Efficient play request dispatching in cloud gaming

机译:让我们一起出发:云游戏中高效的游戏请求分配

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In this paper, we study the problem of how to dispatch the play requests to the cloud servers in a cloud gaming system. We show that the dispatching strategy of play requests may heavily affect the total service cost of the cloud gaming system. The play request dispatching problem can be considered as a variant of the dynamic bin packing problem. However, we show that the classical bin packing algorithms such as First Fit and Best Fit are not efficient in dispatching the play requests in cloud gaming due to the diurnal workload pattern of online games. To address this issue, we propose an efficient request dispatching algorithm that assigns the play requests according to the predicted ending times of the game sessions. Through extensive evaluations using real online gaming traces, we show that the proposed dispatching algorithm can significantly reduce the resource waste of the cloud servers and thus decrease the total service cost compared to the First Fit and Best Fit algorithms.
机译:在本文中,我们研究了如何将游戏请求分配到云游戏系统中的云服务器的问题。我们表明,游戏请求的调度策略可能会严重影响云游戏系统的总服务成本。播放请求分配问题可以视为动态箱包装问题的一种变体。但是,我们显示,由于在线游戏的日工作量模式,诸如First Fit和Best Fit之类的经典bin打包算法在云游戏中分发游戏请求方面效率不高。为了解决这个问题,我们提出了一种有效的请求分配算法,该算法根据预测的游戏会话结束时间分配播放请求。通过使用真实的在线游戏轨迹进行的广泛评估,我们表明,与First Fit和Best Fit算法相比,所提出的调度算法可以显着减少云服务器的资源浪费,从而降低总服务成本。

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