Cost-Optimized Redundant Data Storage in the Cloud

The use of cloud-based storage systems for storing data is a popular alternative to local storage systems. Beside several benefits of cloud-based storages, there are also downsides like vendor lock-in or unavail- ability. Moreover, the selection of the best fitting stor- age solution can be a tedious and cumbersome task and the storage requirements may change over time. In this paper, we formulate a system model that uses multiple cloud-based services to realize a redundant and cost-efficient storage. Within this system model we formulate a local and a global optimization problem that considers historical data access information and predefined Quality of Service requirements to select a cost-efficient storage solution. Furthermore, we present a heuristic optimization approach for the global opti- mization. Extensive evaluations of our approaches we show the benefits of our work in comparison to a base- line that follows a state-of-the-art approach. We show that our approaches save up to 30% of the cumulative cost in comparison to the baseline.
  author = {Waibel, Philipp and Matt, Johannes and Hochreiner, Christoph and Skarlat, Olena and Hans, Ronny and Schulte, Stefan},
  title = {Cost-Optimized Redundant Data Storage in the Cloud},
  journal = {Service Oriented Computing and Applications},
  year = {2017},
  volume = {N},
  number = {N},
  pages = {NN--NN}