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Improved performance of cloud servers using LBSDD factors of private cloud
M. Saravana Karthikeyan, , N. Karthikeyan, S. Karthik
Published in Springer Science and Business Media Deutschland GmbH
Volume: 12
Issue: 6
Pages: 5825 - 5834
The performance of service in cloud environment is a dominant factor which impacts the performance of the entire cloud system. However, the most organizations maintain their own private clouds to maintain their data and enable the access for the users of their own organization. There exist several load balancing and security protocols to access the services and maintain their data in the cloud environment but suffer to achieve higher performance. To handle this issue, Load Balancing, Security, and Data Deduplication (LBSDD) algorithm is presented. Initially, the request received from various users and various locations. Next, request and server related features are extracted. Then, select the best features from the extracted features using HGOA algorithm. After that the LBSDD factors are evaluated for the cloud performance. In evaluation user request is balanced by using Dropbox-NGINX tool with selected features. Next, the user may upload the files to the cloud server, so for providing security is an important factor here the security is maintained by using DKME4C algorithm. Then, the third factor is Data Deduplication evaluated using hashed indexes, tables, here the hash code is generated using the SHA-512 algorithm in this proposed method Data Deduplication is named as E-HIT. The proposed LBSDD algorithm achieves higher performance in server efficiency than other methods. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
About the journal
JournalData powered by TypesetJournal of Ambient Intelligence and Humanized Computing
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH