Time-of-Use pricing policies for offering Cloud Computing as a service

We study a reservation system with finite computing resources over an infinite horizon, where a set of incumbent users submit reservation requests for computing resources ahead in time. Computing resources may be purchased in exchange for tokens. We use the Multinomial Logit (MNL) framework to model customer substitution behavior. Given user requests, the objective is to maximize system performance, defined as the proportion of customers that obtain their preferred time slot, by adjusting resource prices in tokens per unit of time and per computing resource. We consider a class of pricing policies called Time-of-Use (ToU), and propose a simple and intuitive algorithm that is provably optimal for an approximation to our formulated problem. Our proposed solution has the appealing property of flattening demand over the horizon. We evaluate the performance of our approach numerically. For the set of problem instances that we consider, the optimal ToU policy outperforms single pricing strategies by 3-8% for Customer Satisfaction, on average. We discuss the implementation of our proposed approach for Cloud Computing being developed by IBM at the King Abdullah University of Science and Technology (KAUST).