An Efficient Utilization of Storage System Using Text Intersection Based Deduplication in Nano Cloud Environment

The amount of digital data has been increasing exponentially. There is a need to reduce the amount of storage space by storing the data efficiently. In Nano-Cloud storage environment, the data replication provides high availability with fault tolerance system. It takes more memory storage space, by storing duplicate copies of repeated data across multiple servers in the nano-cloud, in order to reduce the storage space, we propose a new novel technique Text Intersection Based Deduplication system at the target level. It is mainly used to detect the popular and unpopular files from large volumes of data files separated geographically a medium is required to reference data at the same time saving storage space for effective utilization of memory space. This proposed approach targets to file level deduplication. After applying text intersection based deduplication the storage space is saved to 27% in this, it is based on multiple instances are more advantages in compared with other existing single instance methods. This approach is more effective to apply the storage concept in nano cloud environment.