On Achieving Cost-Effective Adaptive Cloud Gaming in Geo-Distributed Data Centers

Cloud gaming has become a new trend for gamers to access high-end video games. By rendering games in the remote cloud and streaming video scenes to the users, games can be played anywhere, anytime, on any device (e.g., smartphones, tablets, or personal computers). In this paper, we address the problem of achieving cost-effective adaptive cloud gaming in geo-distributed data centers from the perspective of cloud gaming service providers (CGSPs). Unlike previous work, we consider a cloud gaming system supported with the adaptive streaming technology. Our purpose is to minimize the overall service cost for CGSPs, by adaptively adjusting the selection of data centers, virtual machine allocation and video bitrate configuration for each user. Meanwhile, we also need to ensure good-enough quality of experience (QoE) for gamers. To this objective, we formulate the problem into a constrained stochastic optimization problem, and apply the Lyapunov optimization theory to drive the corresponding online strategy with provable upper bounds. Due to the diverse QoE requirements of video games, we also take the difference among game genres into account during the algorithm design. Finally, we conduct extensive trace-driven simulations to evaluate the effectiveness of our algorithm and our results show that our proposed algorithm can achieve significant gain over other alternative approaches.