A game theoretical model for profit maximization resource allocation in cloud environment with budget and deadline constraints

One significant challenge for the resource allocation in cloud environments is the pricing issue and selection of applicants of cloud resources on the basis of cloud economic parameters. Taking into account the fact that the resource allocation in cloud environments is an economic supply- and demand-based problem, economics-based methods result in better solutions in a shorter period of time. In this paper, using Bayesian method, where each user estimates other rivals’ actions in the next step of the auction, a game model for winner determination is proposed. a non-cooperative game theory mechanism based on combinatorial auction in an environment with incomplete information has been proposed to reach Nash equilibrium point and select the winners. Using the proposed method, an improvement of 17 % profit was obtained for the cloud provider and a 12 % boost was seen in the sold resources. The objective function suggested for bidding converged to the solution in all cases and was stable. In the following, it was proved that the proposed model has the possibility of attaining the best local bid.