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Bio Inspired Algorithms: An Efficient Approach for Resource Scheduling in Cloud Computing

by Gurtej Singh, Amritpal Kaur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 10
Year of Publication: 2015
Authors: Gurtej Singh, Amritpal Kaur
10.5120/20372-2583

Gurtej Singh, Amritpal Kaur . Bio Inspired Algorithms: An Efficient Approach for Resource Scheduling in Cloud Computing. International Journal of Computer Applications. 116, 10 ( April 2015), 16-21. DOI=10.5120/20372-2583

@article{ 10.5120/20372-2583,
author = { Gurtej Singh, Amritpal Kaur },
title = { Bio Inspired Algorithms: An Efficient Approach for Resource Scheduling in Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 10 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 16-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number10/20372-2583/ },
doi = { 10.5120/20372-2583 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:56:43.676357+05:30
%A Gurtej Singh
%A Amritpal Kaur
%T Bio Inspired Algorithms: An Efficient Approach for Resource Scheduling in Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 10
%P 16-21
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Nature plays a vital role in solving complicated problems in computer science. It helps us in finding the optimal desired way to solve extremely dynamic, difficult and robust problems. Bio inspired algorithm help us to cope with the technological need of a new era. Many researchers did enormous work in this area from the past few decades. However, still there is a large more scope for bio inspired algorithm (BIA) in exploring new application and opportunities in cloud computing. This paper presents a broad, detailed in of some Bio inspired algorithm, which was used in order to tackle various challenges faced in Cloud Computing Resource management environment.

References
  1. Dr. Amit Agarwal, Saloni Jain,Mar 2014:Efficient Optimal Algorithm of Task Scheduling in Cloud Computing Environment International Journal of Computer Trends and Technology (IJCTT) – volume 9 number 7.
  2. Anthony T. Velte ,Toby J. Velte ,Robert Elsenpeter ,Cloud computing a practical approach.
  3. Ehsan Valian, Shahram Mohanna and Saeed Tavakoli December 2011 : Improved Cuckoo Search Algorithm for Global Optimization,IJCIT-2011-Vol. 1-No. 1.
  4. Felix Streichert, University of Tuebingen, Introduction to Evolutionary Algorithms.
  5. Ms. D. Thilagavathi and Dr. Antony Selvadoss Thanamani August 2014, Scheduling in High Performance Computing Environment using Firefly Algorithm and Intelligent Water Drop Algorithm, International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 1.
  6. Nitesh Sureja , November 2012:New Inspirations in Nature: A Survey International Journal of Computer Applications & Information Technology Vol. I, Issue III.
  7. Baris Yuce, Michael S. Packianather , Ernesto Mastrocinque , Duc Truong Pham November 2013, Alfredo Lambiase 3Honey Bees Inspired Optimization Method: The Bees Algorithm,ISSN 2075-4450.
  8. Sankalap Arora,Satvir Singh,May 2013 :The Firefly Optimization Algorithm: Convergence Analysis and Parameter Selection, International Journal of Computer Applications (0975 – 8887)Volume 69– No. 3.
  9. Xin-She Yanga, Mehmet Karamanoglua, Xingshi Heb , Year 2013: Multi-objective Flower Algorithm for Optimization, International Conference on Computational Science, ICCS 2013.
  10. S. D. Shtovba, March 2004 : Ant Algorithms Theory and Applications, Vol. 31, No. 4, 2005.
  11. O. Abdel-Raouf, M. Abdel-Baset, I. El-henawy,February 2014:A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems, International Journal of Applied Operational Research Vol. 4, No. 2, pp. 1-13.
  12. Ashish Gosh , Satchidananda Dehuri , Aprail 2004: Evolutionary Algorithm for Multi Criterion Optimization : A Survey , Volume2,International Journals of Computing and Information Science.
  13. Sangita Roy,Sheli Sinha Chaudhuri,Year 2013:Cuckoo Search Algorithm using Lèvy Flight: A Review,I. J. Modern Education and Computer Science.
  14. Koza, J. R. (1992). "Genetic Programming:on the programming of Computers by means of natural selection " MIT Press.
  15. http://www. mhhe. com/biosci/pae/botany/botany_map/articles/article_01. html.
  16. Xin-She Yang, Nature-Inspired Optimization Algorithms, School of Science and Technology, Middlesex University London, London.
  17. David Alejandro Pelta,Natalio Krasnogor ,Dan Dumitrescu ,Camalia Chira ,Rodica Lung ,Natural Inspired Cooperative Strategies for Optimization (NICSO2011).
  18. Melanie Mitchell, An introduction to genetic algorithm.
Index Terms

Computer Science
Information Sciences

Keywords

Genetic Algorithm (GA) Genetic Programming (GP) Ant Colony (AC) Firefly (FF) Flower Pollination (FP) Cuckoo Search (CS) Honey Bee (HB).

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