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

by Gurtej Singh, Amritpal Kaur
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

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 = { },
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

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.

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Index Terms

Computer Science
Information Sciences


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