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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.


Solution components.
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Related In: Results  -  Collection


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fig9: Solution components.

Mentions: The components of the solution are shown in Figure 9. The main components are the client who initiates the request and sends it to the cloud, the load balancer which checks the file download experiences from the database and assigns tasks to the Cloud servers, the servers which process the requests, and the file controller which partitions the files at the storage level after checking the experiences of the file downloads. Our technique worked well when all servers are running well and processing their assigned tasks. However, we are in the process of analyzing the situation when one or multiple servers fail. In this case, we need to have more replicated file partitions as backup. This will be implemented in our future work.


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

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

Solution components.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig9: Solution components.
Mentions: The components of the solution are shown in Figure 9. The main components are the client who initiates the request and sends it to the cloud, the load balancer which checks the file download experiences from the database and assigns tasks to the Cloud servers, the servers which process the requests, and the file controller which partitions the files at the storage level after checking the experiences of the file downloads. Our technique worked well when all servers are running well and processing their assigned tasks. However, we are in the process of analyzing the situation when one or multiple servers fail. In this case, we need to have more replicated file partitions as backup. This will be implemented in our future work.

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.