DOIONLINE 
DOIONLINE Publish In |
International Journal of Management and Applied Science (IJMAS)-IJMAS |
 Journal Home Volume Issue |
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Issue |
Volume-4,Issue-6 ( Jun, 2018 ) | |||||||||
Paper Title |
Performance Evaluation of Multilevel Storage Optimization using Dimension Reduction and Compression Framework in Distributed Clusters | |||||||||
Author Name |
N. S. Kalyan Chakravarthy, N. Sudhakar, E. Srinivasa Reddy, D. Venkata Subramanian, P. Shankar | |||||||||
Affilition |
Resesarch Scholar, Department of Computer Science, University College of Engineering & Technology, Acharya Nagarjuna University Professor, Department of Computer Science, Bapatla Engineering College Principal, University College of Engineering & Technology, Acharya Nagarjuna University Adjunct Professor, QIS College of Engineering and Technology, Department of CSE, Ongole, A.P Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation, Chennai | |||||||||
Pages |
32-36 | |||||||||
Abstract |
The increase in the volume of Big Data and IoT environments are due to different types and complexity of data generated from multiple sources especially from sensors and IoT devices. There are many proven dimension reduction techniques and data compression techniques evolved over last two decades. This paper provides brief overview of some of the critical steps to apply PCA and Erasure Codes in Hadoop Environment and also how Multilevel Storage Optimization is a good approach when compared with other storage compression techniques and dimension reduction techniques. The case study and evaluation proved that the performance of the framework is better in terms of number of blocks, utilization of CPU, Memory, IO and storage efficiency. Keywords - Evaluation, Performance, MLSO-DRAC, Framework, Storage, Erasure, PCA | |||||||||
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