TY - GEN
T1 - Time-of-Use pricing policies for offering Cloud Computing as a service
AU - Saure, Denis
AU - Sheopuri, Anshul
AU - Qu, Huiming
AU - Jamjoom, Hani
AU - Zeevi, Assaf
PY - 2010
Y1 - 2010
N2 - 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 jlattening 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 mM at the King Abdullah University of Science and Technology (KAUST).
AB - 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 jlattening 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 mM at the King Abdullah University of Science and Technology (KAUST).
UR - http://www.scopus.com/inward/record.url?scp=77957785832&partnerID=8YFLogxK
U2 - 10.1109/SOLI.2010.5551564
DO - 10.1109/SOLI.2010.5551564
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AN - SCOPUS:77957785832
SN - 9781424471188
T3 - Proceedings of 2010 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2010
SP - 300
EP - 305
BT - Proceedings of 2010 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2010
Y2 - 15 July 2010 through 17 July 2010
ER -