Issue No. 09 - September (2011 vol. 23)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2011.35
Verena Kantere , Ecole Polytechnique Fédérale de Lausanne, Lausanne
Debabrata Dash , ArcSight, an HP Company, Cupertino
Grégory François , Ecole Polytechnique Fédérale de Lausanne, Lausanne
Sofia Kyriakopoulou , Ecole Polytechnique Fédérale de Lausanne, Lausanne
Anastasia Ailamaki , Ecole Polytechnique Fédérale de Lausanne, Lausanne
Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. The users can query the cloud data, paying the price for the infrastructure they use. Cloud management necessitates an economy that manages the service of multiple users in an efficient, but also, resource-economic way that allows for cloud profit. Naturally, the maximization of cloud profit given some guarantees for user satisfaction presumes an appropriate price-demand model that enables optimal pricing of query services. The model should be plausible in that it reflects the correlation of cache structures involved in the queries. Optimal pricing is achieved based on a dynamic pricing scheme that adapts to time changes. This paper proposes a novel price-demand model designed for a cloud cache and a dynamic pricing scheme for queries executed in the cloud cache. The pricing solution employs a novel method that estimates the correlations of the cache services in an time-efficient manner. The experimental study shows the efficiency of the solution.
Cloud data management, data services, cloud service pricing.
Verena Kantere, Debabrata Dash, Grégory François, Sofia Kyriakopoulou, Anastasia Ailamaki, "Optimal Service Pricing for a Cloud Cache", IEEE Transactions on Knowledge & Data Engineering, vol. 23, no. , pp. 1345-1358, September 2011, doi:10.1109/TKDE.2011.35