title: Partial storage optimization and load control strategy of cloud data centers.
abstract: We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner.
authors.affiliation: UAE University, P.O. Box 15551, Al Ain, UAE.
authors.forename: Klaithem
authors.identifier: 0000-0002-5099-9719
authors.initials: K
authors.lastname: Al Nuaimi
authors.affiliation: UAE University, P.O. Box 15551, Al Ain, UAE.
authors.forename: Nader
authors.identifier: 0000-0002-5686-7848
authors.initials: N
authors.lastname: Mohamed
authors.affiliation: UAE University, P.O. Box 15551, Al Ain, UAE.
authors.forename: Mariam
authors.identifier: 0000-0002-1184-1118
authors.initials: M
authors.lastname: Al Nuaimi
authors.affiliation: University of Pittsburgh, Pittsburgh, PA 15260, USA.
authors.forename: Jameela
authors.identifier: 0000-0003-1376-0052
authors.initials: J
authors.lastname: Al-Jaroodi