Cloud Storage and Processing Service Selection considering Tiered Pricing and Data Regulations

Most countries have come up with varied data privacy regulations. Some countries have stringent data storage and processing regulations, while others allow conditional data transfer across borders. For enterprises with geographically distributed data sources (users), it becomes challenging to select cloud data centers that meet data regulations and have minimal overall operational costs. In this work, we propose a joint optimization model for the selection of storage and processing services from multiple cloud service providers, taking into practical consideration of data regulations and tiered pricing, which has not been addressed in the prior art. To solve this hard multi-objective combinatorial optimization problem, we propose a greedy cost-reductionbased algorithm. The proposed algorithm gives multiple nondominating solutions, which are on average 2.5% away from the optimal solution. Further, we demonstrate the implications of data regulations and the benefits of joint optimization.