Research Article
Increasing the Reliability of Fuzzy Angle Oriented Cluster Using Peer-to-Peer
@INPROCEEDINGS{10.1007/978-3-642-37949-9_80, author={Remani Naga Venkata Jagan Mohan and Vegi Srinivas and Kurra Rajasekhara Rao}, title={Increasing the Reliability of Fuzzy Angle Oriented Cluster Using Peer-to-Peer}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Networks. 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers}, proceedings_a={QSHINE}, year={2013}, month={7}, keywords={Angle Oriented Fuzzy Cluster MapReduce Peer-to-Peer Quality of Service}, doi={10.1007/978-3-642-37949-9_80} }- Remani Naga Venkata Jagan Mohan
Vegi Srinivas
Kurra Rajasekhara Rao
Year: 2013
Increasing the Reliability of Fuzzy Angle Oriented Cluster Using Peer-to-Peer
QSHINE
Springer
DOI: 10.1007/978-3-642-37949-9_80
Abstract
The vast volume of data is collected and it needs to be analyzed rapidly for Quality of Data and Quality of Service (QoS), both are used for verification of sharing the information not only for web applications, but also used for many user applications over a network. In this paper, we proposed MapReduce (i.e., Parallelized and Distributed) process used for improving the performance of peer to peer communication on angle oriented clusters in Big Data. To study of this paper, the data set classified into two types namely, Clock wise and Anti-clock wise rotations using Fuzzy cluster classification. The data is extracted by using the angle oriented DCT (Discrete Cosine Transform) that invokes certain normalization techniques. Also, matching the data is compared with the technique of similarity based approach using Tanimatto distance. A high recognition rate is observed using Nelson model for this approach, and it is proved by giving an example.