Welcome to the InfoSci Platform
User Opinion and Differentiated Attribute based Ranking in Federated Cloud

User Opinion and Differentiated Attribute based Ranking in Federated Cloud

C. S. Rajarajeswari, M. Aramudhan
Copyright: © 2016 |Volume: 9 |Issue: 2 |Pages: 11
ISSN: 1938-7857|EISSN: 1938-7865|EISBN13: 9781466689831|DOI: 10.4018/JITR.2016040104
Cite Article Cite Article

MLA

Rajarajeswari, C. S., and M. Aramudhan. "User Opinion and Differentiated Attribute based Ranking in Federated Cloud." JITR vol.9, no.2 2016: pp.78-88. http://doi.org/10.4018/JITR.2016040104

APA

Rajarajeswari, C. S. & Aramudhan, M. (2016). User Opinion and Differentiated Attribute based Ranking in Federated Cloud. Journal of Information Technology Research (JITR), 9(2), 78-88. http://doi.org/10.4018/JITR.2016040104

Chicago

Rajarajeswari, C. S., and M. Aramudhan. "User Opinion and Differentiated Attribute based Ranking in Federated Cloud," Journal of Information Technology Research (JITR) 9, no.2: 78-88. http://doi.org/10.4018/JITR.2016040104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Cloud computing is an innovative technology which provides services to users on-demand and pay per use. Since there are many providers in cloud, users get confused in selecting the optimal service provider for their tasks. To overcome this limitation, federated cloud management architecture was proposed. The proposed work provides a new federated cloud mechanism, in which Broker Manager takes the responsibility of providing optimal and ranked service provider for user requirements. To rank the service providers in the federated cloud, Differentiated Priority based Ranking algorithm is implemented at the level of BM. Attributes are differentiated based on their weights assigned by a user. Service providers are discovered and ranked based on the differentiated attributes. The proposed algorithm chooses the cloud service provider for execution, not only based on the rank list generated by the BM; but also based on the suggestion given by the user. The experimental result shows that the proposed algorithm improves the performance of resource provisioning than the existing model by 13%.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.