Optimized and Secure Multiple Predictions Based Traffic Redundancy Elimination - A Survey

Authors(2) :-Anto Viji A, Dr.J.Jasper

Cloud computing is a specific term that involves delivering hosted services over the Internet, Cloud offers various types of on demand services that enable users to access simultaneous computing capabilities. Traffic Redundancy elimination is the most common factor in cloud computing. Cloud Computing involves mostly based on the concepts of high performance computing. Cloud Storage delivers virtualized storage on demand, over a network based on a request for a given quality of service. Redundancy elimination can be enhanced by mutual perceptive between the sender and receiver. Using either sender-based TRE or receiver-based TRE cannot simultaneously capture traffic redundancy in both short-term) and long-term data redundancy, which concurrently appear in the traffic. Cloud security is a major risk factor in cloud computing. In order to enhance the security and elimination of redundant data can be done by a novel proposed algorithm based on neural network schema.

Authors and Affiliations

Anto Viji A
M.E Reseach Scholar, CSI Institute of Technology, Thovalai, Tamil Nadu, India
Ph.D, Department of Electrical and Electronics Engineering, Ponjesly College of Engineering, Nagercoil, Tamil Nadu, India

Cloud Computing, Neural Networks, Traffic redundancy Elimination, Optimization

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Publication Details

Published in : Volume 4 | Issue 8 | May-June 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 377-382
Manuscript Number : IJSRST184884
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Anto Viji A, Dr.J.Jasper, " Optimized and Secure Multiple Predictions Based Traffic Redundancy Elimination - A Survey", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 4, Issue 8, pp.377-382, May-June-2018.
Journal URL : http://ijsrst.com/IJSRST184884

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