Efficient Nash equilibrium resource allocation based on game theory mechanism in cloud computing by using auction

Due to the widespread use of cloud services, the need for proper and dynamic distribution will redouble the resources. One of the most complex problems in cloud environments is resource allocation such that on one hand the resource provider should obtain maximum utilization and on the other hand users want to lease best resources based on his time and budget constraints. Many studies which presented new methods for solving this NP-complete problem have used heuristic algorithm. Based on economic aspects of cloud environments, using market oriented model for solving allocation problem can decrease the complexity and converge it to the best solution in minimum time. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneers utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider.