Minimal Cost Data Sets Storage in the Cloud?

Scientists are able to deploy computation and data intensive applications using massive computation power and storage capacity of cloud computing systems. These applications can be deployed without infrastructure investment. Cloud can be used to store large application data sets. For cost-effectively storing large volume of generated data sets in clouds, development of storage strategies and bench marking approaches have done based on the pay-as-you-go model. But they are either impractical at run time or inadequately cost-effective for storage. In this paper, a novel high cost-effective and practical storage strategy is proposed to achieve a minimum cost bench mark. Here in this proposed strategy, it can automatically decide if at run time or not the storing of generated data must be done or not. Local-optimization for the tradeoff between computation and storage is the primary objective of this strategy. Secondary objective is to take into consideration the users’ preference on storage. In this paper we manage both original and generated data storage. Also we use data compression for the efficient cost effective data storage in Cloud.