Maximizing revenue with dynamic cloud pricing: The infinite horizon case

We study the infinite horizon dynamic pricing problem for an infrastructure cloud provider in the emerging cloud computing paradigm. The cloud provider, such as Amazon, provides computing capacity in the form of virtual instances and charges customers a time-varying price for the period they use the instances. The provider's problem is then to find an optimal pricing policy, in face of stochastic demand arrivals and departures, so that the average expected revenue is maximized in the long run. We adopt a revenue management framework to tackle the problem. Optimality conditions and structural results are obtained for our stochastic formulation, which yield insights on the optimal pricing strategy. Numerical results verify our analysis and reveal additional properties of optimal pricing policies for the infinite horizon case.

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