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Partial storage optimization and load control strategy of cloud data centers.

Al Nuaimi K, Mohamed N, Al Nuaimi M, Al-Jaroodi J - ScientificWorldJournal (2015)

Bottom Line: Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud.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.

View Article: PubMed Central - PubMed

Affiliation: UAE University, P.O. Box 15551, Al Ain, UAE.

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.

No MeSH data available.


DaaS structure.
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Related In: Results  -  Collection


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fig2: DaaS structure.

Mentions: DaaS [8] as mentioned earlier stands for data as a service. Providing data as a service on the cloud means enabling organizations to provide some common and needed data for different cloud users. This data is made available on some cloud servers. Generally back-end processes of assigning tasks to servers and downloading data from them is hidden from the end users because it is not of interest for them. DaaS is also viewed in [9] as providing data in different formats for different resources in various geographical locations. The resources would be able to upload, download, and edit the data on the cloud based on their assigned privileges. Usually, the cloud has multiple distributed servers which are able to access the data centers and fetch the data from them. Figure 2 shows how the cloud DaaS is usually structured.


Partial storage optimization and load control strategy of cloud data centers.

Al Nuaimi K, Mohamed N, Al Nuaimi M, Al-Jaroodi J - ScientificWorldJournal (2015)

DaaS structure.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4417988&req=5

fig2: DaaS structure.
Mentions: DaaS [8] as mentioned earlier stands for data as a service. Providing data as a service on the cloud means enabling organizations to provide some common and needed data for different cloud users. This data is made available on some cloud servers. Generally back-end processes of assigning tasks to servers and downloading data from them is hidden from the end users because it is not of interest for them. DaaS is also viewed in [9] as providing data in different formats for different resources in various geographical locations. The resources would be able to upload, download, and edit the data on the cloud based on their assigned privileges. Usually, the cloud has multiple distributed servers which are able to access the data centers and fetch the data from them. Figure 2 shows how the cloud DaaS is usually structured.

Bottom Line: Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud.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.

View Article: PubMed Central - PubMed

Affiliation: UAE University, P.O. Box 15551, Al Ain, UAE.

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.

No MeSH data available.