Cost-Efficient Server Provisioning for Cloud Gaming

Cloud gaming has gained significant popularity recently due to many important benefits such as removal of device constraints, instant-on, and cross-platform. The properties of intensive resource demands and dynamic workloads make cloud gaming appropriate to be supported by an elastic cloud platform. Facing a large user population, a fundamental problem is how to provide satisfactory cloud gaming service at modest cost. We observe that the software storage cost could be substantial compared to the server running cost in cloud gaming using elastic cloud resources. Therefore, in this article, we address the server provisioning problem for cloud gaming to optimize both the server running cost and the software storage cost. We find that the distribution of game software among servers and the selection of server types both trigger tradeoffs between the software storage cost and the server running cost in cloud gaming. We formulate the problem with a stochastic model and employ queueing theory to conduct a solid theoretical analysis of the system behaviors under different request dispatching policies. We then propose several classes of algorithms to approximate the optimal solution. The proposed algorithms are evaluated by extensive experiments using real-world parameters. The results show that the proposed Ordered and Genetic algorithms are computationally efficient, nearly cost-optimal, and highly robust to dynamic changes.