Distributed Hash Table for Load Balancing of Cloud Backup Services with Local-Global Source Deduplication and in Personal Storage

The concept of the Cloud computing has significantly changed the field of parallel and distributed computing systems today. Cloud computing enables a wide range of users to access distributed, scalable, virtualized hardware and/or software infrastructure over the Internet. So the centralized cloud management was developed in earlier years to satisfy the efficiency and cost inflection point which offers simple offsite storage for disaster recovery, which is always a critical concern for data backup. To prepare one alternative, Cloud backup service is a best choice which is cost-effective and provides protection to personal computing devices or cloud storage. In cloud backup services with recent advent of technology, resource control or load balancing in cloud computing is main challenging issue. The proposed method will focus on the following factors, user provisioning cost, security to storage, load balancing, and avoid redundancy. For providing these factors, the functions to perform are de-duplication process, chunking of data, hash function, load balancing and Application aware. The de-duplication process performs the functions local de-duplication and global de-duplication to check the local cloud storage and the global cloud storage, which gives more effectiveness and latency of de-duplication. An intelligent data chunking method and Hash functions are performed, which splits the files into the chunks of data and apply hash functions to those chunks of data, which results in minimal computational overhead and high security to the cloud storage. Load balancing function is used to balance the load while storing the files into the resources of cloud. Propose a simple fully distributed scheme which works in a constant number of rounds and achieves optimal balance with high probability. The total number of migrations is within a constant factor from the number of migrations generated by the optimal centralized algorithm. . In order to gain maximum profits with optimized load balancing algorithms, it is necessary to utilize resources efficiently. Perform experiments via prototype implementation to demonstrate that proposed scheme can significantly improve deduplication efficiency over the state-of-the-art methods with low system overhead, highly balanced system and more security.