Enhancing the data retrieval in hybrid cloud

Abstract

The cloud computing environment facilitates diversified number of potential services to its users such as the utilized-based pricing, on demand service utilization and risk transference during the process of resource sharing. However, the security to cloud services during the event of data sharing is considered as the crucial task. Establishing a set of strict privacy requirement for the secure cloud data utilization is essential to implement the security system in the real time environment. The data retrieval in cloud environment is a time consuming process. In addition, providing privacy of the data from the cloud makes it more tedious. The chapter investigates the two algorithms for providing the security in the cloud environment. Two significant approaches such as Secure Retrieval Process over Cloud Data using Improved Privacy Multi-Keyword Retrieval Scheme (IPMKRS) and Hilbert Space Filling Curve Retrieval Scheme (HSFCRS) are presented for analyzing its significance in improving the security in the retrieval process. The potential entities which are identified form the components of the cloud based on two ranking techniques and further then optimal fault tolerance scheme is implemented for choosing the optimal fault tolerance technique suitable for each of the cloud components. The Component ranking framework is defined to identify the cloud component by selecting the optimal cloud service among the cloud service provider. Component Ranking Forecasting Scheme for Scheduling Fault Tolerance (CRFS-SFT) uses a framework that initially inspires component ranking for automatically prioritizing the components of the cloud applications. newline