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Intelligent Linear Data Structure with Self Performance Optimization Capacity: Application on Big Data

by Smail Tigani, Mouhamed Ouzzif, Abderrahim Hasbi, Rachid Saadane
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 101 - Number 6
Year of Publication: 2014
Authors: Smail Tigani, Mouhamed Ouzzif, Abderrahim Hasbi, Rachid Saadane
10.5120/17688-8635

Smail Tigani, Mouhamed Ouzzif, Abderrahim Hasbi, Rachid Saadane . Intelligent Linear Data Structure with Self Performance Optimization Capacity: Application on Big Data. International Journal of Computer Applications. 101, 6 ( September 2014), 1-6. DOI=10.5120/17688-8635

@article{ 10.5120/17688-8635,
author = { Smail Tigani, Mouhamed Ouzzif, Abderrahim Hasbi, Rachid Saadane },
title = { Intelligent Linear Data Structure with Self Performance Optimization Capacity: Application on Big Data },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 101 },
number = { 6 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume101/number6/17688-8635/ },
doi = { 10.5120/17688-8635 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:31:54.491246+05:30
%A Smail Tigani
%A Mouhamed Ouzzif
%A Abderrahim Hasbi
%A Rachid Saadane
%T Intelligent Linear Data Structure with Self Performance Optimization Capacity: Application on Big Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 101
%N 6
%P 1-6
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The access to relevant information from a big data container is gaining immense significance. This depends on storage technics and the organization level. This work proposes an intelligent linear data structure with an integrated cognitive agent reorganizing periodically the data structure content. The reorganization is based on a confidence interval of a random variable estimated by the agent. This random variable represents the demand frequency for each element. The cognitive agent studies the client behavior and puts most popular data in the beginning of the array in order to be found quickly. That increases considerably the search algorithm performance and solves by that one of most problems of the big data field. Models and algorithms in this work are implemented with Java programming language and simulated and that proves the reliability of the approach.

References
  1. Z. Yang, J. Tian and Y. Dai, Towards a more accurate availability evaluation in peer-to-peer storage systems, International Journal of High Performance Computing and Networking, Vol. 6, Nos. 3/4, 2010.
  2. I. Ioannidis, A. Grama and M. Atallah, Adaptive Data Structures for IP Lookups, IEEE INFOCOM, Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies, Vol. 1, pp 75 - 84, 2003.
  3. R. Gupta, Journey from Data Mining to Web Mining to Big Data, International Journal of Computer Trends and Technology, Vol. 10, No. 1, October 2014.
  4. A. Habibizad Navin, M. Naghian Fesharaki, M. K. Mirnia and M. Teshnelab, A Novel Method for Improving the Uniformity of Random Number Generator Based on Data Oriented Modeling, International Journal of Computer Science and Network Security, Vol. 7 No. 7, July 2007, pp 269-273.
  5. K. Greer, M. Baumgarten, M. Mulvenna and C. Nugent, An infrastructure for developing self-organising services, International Journal of Adaptive and Innovative Systems, Vol. 1, No. 1, 2009, pp 88-103.
  6. M. Beck Rutzig and A. Carlos Schneider Beck, An infrastructure for developing self-organising services, International Journal of High Performance Systems Architecture, Vol. 4, No. 1, 2012, pp 13-24.
  7. D. Lefebvre, Introduction : Some challenges for adaptive and innovative systems in the next future, International Journal of Adaptive and Innovative Systems, Vol. 1, No. 1, 2009, pp 1- 12.
  8. M. Tanusit, Two-Side Confidence Intervals for the Poisson Means, International Journal of Modeling and Optimization, Vol. 2, No. 5, October 2012.
  9. S. Niwitpong and S. Niwitpong, On Simple Confidence Intervals for the Normal Mean with a Known Coefficient of Variation, International Journal of Mathematical, Computational, Physical and Quantum Engineering Vol:7 No:9, 2013, pp 1- 12.
  10. M. Tanusit, A Novel Method for Improving the Uniformity of Random Number Generator Based on Data Oriented Modeling, International Journal of Computer Science and Network Security, Vol. 7 No. 7, July 2007, pp 269-273.
  11. L. Lebart, A. Morineay and M. Piron, Statistique Exploratoire Multidimensionnelle, ISBN 2 10 0028863, Dunod, Paris, 1995.
  12. K. Ranga, N. Kumar and M. Reddy, Generation of standard normal random variables, Indian Journal of Scientific Research, No. 4, Vol. 2, pp. 83-85, 2011.
  13. B. Eckel, Thinking in Java 4th Edition,ISBN 978- 0131872486, Prentice Hall, 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Data Structures Big Data Statistic Modelling Algorithms and Computational Complexity Auto-adaptive Systems High Performance Systems.

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