Budget constrained selection of cloud storage services for advanced processing in datacenters

Large scale, cyber-infrastructure systems include a large base of heterogeneous data sources, geographically distributed. Cloud storage services can be an ideal candidate for storing all these data. However, it is difficult to find the optimal solution in order to select a set of storage providers, with respect to different multiple objectives of this type of systems, such as cost optimization, budget constraints, Quality of Service (QoS), load balancing etc. In this paper, we study the multi-objective optimization problem for storage service selection with budget constraints. We start from a real world case scenario and build our mathematical model for the optimization problem. Then we propose a linear programming technique to find a near optimal solution for the service selection problem.