Cloud computing providers offer two different pricing schemes when renting virtual machines: reserved instances and ondemand instances. On-demand instances are paid only when utilized and they are useful to satisfy a fluctuating demand. Conversely, reserved instances are paid for a certain time period and are independent of usage. Since reserved instances require more commitment from users, they are cheaper than on-demand instances. However, in order to be cost-effective compared to on-demand instances, they have to be extensively utilized. This work focuses on finding the optimal combination of on-demand and reserved instances, such that the demand is satisfied and the costs minimized. To achieve this goal, this study introduces a stochastic model of the resources, based on Inventory Theory. The idea is to formulate the optimization problem as an inventory-keeping problem and then derive the optimal strategy. The paper evaluates the proposed model using data from an industry case, comparing the performance with a brute-force approach. The conducted experiments show that the Inventory Theory model provides accurate results and potentially allows prior research on Inventory Theory to be applied to optimal cloud provisioning.
|Title of host publication||Proceedings of the 31st Annual ACM Symposium on Applied Computing - SAC '16|
|Place of Publication||New York, New York, USA|
|Publisher||Association for Computing Machinery ACM|
|Number of pages||4|
|Publication status||Published - 2016|
|MoE publication type||A4 Article in a conference publication|
Nodari, A., Nurminen, J. K., & Frühwirth, C. (2016). Inventory theory applied to cost optimization in cloud computing. In Proceedings of the 31st Annual ACM Symposium on Applied Computing - SAC '16 (pp. 470-473). Association for Computing Machinery ACM. https://doi.org/10.1145/2851613.2851869