Cloud computing enables larger classes of application service providers to distribute their services to world-wide users in multiple regions without their own private data centers. Heterogeneity and resource limitation of geo-graphically distributed cloud data centers impose application service providers to have incentives to optimize their computing resource usage while guaranteeing some level of quality of service. Recent studies proposed various techniques for optimization of computing resource usage from cloud users (or application service providers) perspective with little consideration of competition. In addition, optimization efforts of application service providers motivate cloud service providers owning multiple geo-distributed clouds to decide their computing resource prices considering their efforts. In this context, we formulate this problem for cloud service providers as a game of resource pricing in geo-distributed clouds. One of the main challenges in this problem is how to model the best responses of application service providers, given resource price information of clouds in non-overlapped regions. We propose a novel concave game to describe the quantity competition among application service providers reducing payment while guaranteeing fair service delay to end users. Furthermore, we optimize the prices of computing resources to converge to the equilibrium. In addition, we show several characteristics of the equilibrium point and discuss their implications to design computing resource markets for geo-distributed clouds.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.