Towards Minimizing Resource Usage With QoS Guarantee in Cloud Gaming

Abstract

Cloud gaming has been very popular recently, but providing satisfactory gaming experiences to players at a modest cost is still challenging. Colocating several games onto one server could improve server utilization. However, prior work regarding colocating games either ignores the performance interference between games or uses simple performance model to charaterize it, which may make inefficient game colocation decisions and cause QoS violations. In this article, we address the resource allocation issues for colocating games in cloud gaming. We first propose a novel machine learning-based performance model, which is able to capture the complex relationship among the performance interference, the contention features of colocated games and resource partition. Guided by the performance model, we then propose efficient and effective algorithms for two resource allocation scenarios in cloud gaming. We evaluate the proposed solutions through extensive experiments using a large number of real popular games. The results show that our performance model is able to identify whether a colocated game satisfies QoS requirement within an average error of 5 percent, which significantly outperforms the alternatives. Our resource allocation algorithms are able to increase the resource utilization by up to 60 percent compared to the state-of-the-art solutions.