Cloud is an emerging technology that stores the necessary data and electronic form of data is produced in gigantic quantity. It is vital to maintain the efficacy of this data the need of data recovery services is highly essential. Cloud computing is anticipated as the vital foundation for the creation of IT enterprise and it is an impeccable solution to move databases and application software to big data centers where managing data and services is not completely reliable. Our focus will be on the cloud data storage security which is a vital feature when it comes to giving quality service. It should also be noted that cloud environment comprises of extremely dynamic and heterogeneous environment and because of high scale physical data and resources, the failure of data centre nodes is completely normal.Therefore, cloud environment needs effective adaptive management of data replication to handle the indispensable characteristic of the cloud environment. Disaster recovery using cloud resources is an attractive approach and data replication strategy which attentively helps to choose the data files for replication and the strategy proposed tells dynamically about the number of replicas and effective data nodes for replication. Thus, the objective of future algorithm is useful to help users together the information from a remote location where network connectivity is absent and secondly to recover files in case it gets deleted or wrecked because of any reason. Even, time oriented problems are getting resolved so in less time recovery process is executed.
Adaptive Data Replication Optimization Based on Reinforcement Learning