A Novel Data Set Importance Based Cost-Effective and Computation-Efficient Storage Strategy in the Cloud

The rapid development of cloud computing service allows data and computation intensive applications to be easily moved into cloud. Users pay for computing and storing resources to deal with their data in the cloud, therefore how to manage those resources has become an important issue. In order to satisfy different demands of users, various storage strategies have been proposed. Aiming at presenting a cost-effective and computation-efficient strategy, the paper considers both the monetary cost and response time to decide whether a generated data set should be stored or not based on the proposed data importance model. The main focus of this model is to compare the attributes and relationships between data sets. To better illustrate the effectiveness and efficiency of our strategy, both theoretical analysis and simulations are conducted in this paper. Various experiments show excellent results that our strategy outperforms its counterparts in both cost and computation.