Competitive Markov decision processes
Competitive Markov decision processes
Scheduling Parallel Cloud Computing Services: An Evolutional Game
ICISE '09 Proceedings of the 2009 First IEEE International Conference on Information Science and Engineering
Analysis of duopoly price competition between WLAN providers
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Pricing and Dimensioning Competing Large-Scale Service Providers
Manufacturing & Service Operations Management
Price-based user-optimal job allocation scheme for grid systems
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Resource and Revenue Sharing with Coalition Formation of Cloud Providers: Game Theoretic Approach
CCGRID '11 Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
Pricing cloud bandwidth reservations under demand uncertainty
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
The pricing model of cloud computing services
Proceedings of the 14th Annual International Conference on Electronic Commerce
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With many providers in today's cloud market, it is crucial for each provider to offer an optimal price policy which maximizes the final revenue and improves the competitive advantage. The competition among providers leads to the evolution of the market and dynamic resource prices over time. In this paper, we address the competition among cloud providers and propose a dynamic pricing scheme. We employ a discrete choice model to describe the user's behavior. The model is used to derive the probability of a user choosing to be served by a certain provider. The competition among cloud providers is formulated as a non-cooperative stochastic game where the players are providers who act by proposing the price policy simultaneously. The game is modelled as a Markov Decision Process whose solution is a Markov Perfect Equilibrium. Numerical simulations are carried out to evaluate the performance of the proposed model.