CFP last date
20 January 2025
Reseach Article

Task based approach towards Load Balancing in Cloud Environment

by Rajani S. Sajjan, Rekha Y. Biradar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 31
Year of Publication: 2018
Authors: Rajani S. Sajjan, Rekha Y. Biradar
10.5120/ijca2018916714

Rajani S. Sajjan, Rekha Y. Biradar . Task based approach towards Load Balancing in Cloud Environment. International Journal of Computer Applications. 179, 31 ( Apr 2018), 39-43. DOI=10.5120/ijca2018916714

@article{ 10.5120/ijca2018916714,
author = { Rajani S. Sajjan, Rekha Y. Biradar },
title = { Task based approach towards Load Balancing in Cloud Environment },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2018 },
volume = { 179 },
number = { 31 },
month = { Apr },
year = { 2018 },
issn = { 0975-8887 },
pages = { 39-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number31/29198-2018916714/ },
doi = { 10.5120/ijca2018916714 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:57:10.898082+05:30
%A Rajani S. Sajjan
%A Rekha Y. Biradar
%T Task based approach towards Load Balancing in Cloud Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 31
%P 39-43
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Load balancing is all time trending topic in a cloud environment. In order to improve system performance and to protect the system against failures, the workload must be distributed among one or more server efficiently and dynamically. In this paper, we propose a Task based Approach towards Load Balancing (TB-LB) in a Cloud Environment based on clustering of virtual machines and heuristic algorithms. The proposed system is used to solve both the population based and non-population based problems. The proposed system combines three heuristic algorithms, namely simulated annealing, particle swarm optimization and genetic algorithm to balance the load and to minimize the makespan of tasks and system performance by considering the task requirement. It also uses k-means clustering approach to organize virtual machines (VMs) into groups to reduce the execution time. The simulation results show that our proposed algorithm improves the system performance by minimizing makespan and execution time

References
  1. Sajjan R.S, Biradar Rekha Yashwantrao, Torvi Harshal. Enterprise Architecture and Services in Cloud Computing: A Survey. International Journal of Computer Sciences and Engineering Vol.-4, Special Issue-4, Jun 2016, pp.28-34.
  2. Sajjan R.S, Biradar Rekha Yashwantrao. Load Balancing and its Algorithms in Cloud Computing: A Survey. International Journal of Computer Sciences and Engineering Vol.-5(1), Jan 2017, pp.95-100.
  3. Peter Mell, Timothy Grance. The NIST Definition of Cloud Computing. National Institute of Standards and Technology Special Publication 800-145(September 2011).
  4. Geetinderkaur and Sarabjitkaur. Improved Hyper-Heuristic Scheduling with Load-Balancing and RASA for Cloud Computing Systems. International Journal of Grid and Distributed Computing Vol. 9, No. 1 (2016), pp.13-24.
  5. Deepa.K, Prabhu.S, Dr.N.Sengottaiyan. A Hyper-Heuristic Method for scheduling the jobs in Cloud Environment. Informatics Engineering, an International Journal (IEIJ), Vol.4, No.1, March 2016, pp. 23-31.
  6. http://www.obitko.com/tutorials/genetic-algorithms/ga-basic-description.php
  7. M. Lagwal and N. Bhardwaj, "Load balancing in cloud computing using genetic algorithm," 2017 International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, 2017, pp. 560-565.
  8. Leszek Sliwko and Vladimir Getov, “A Meta-Heuristic Load Balancer for Cloud Computing Systems” ,2015 IEEE 39th Annual International Computers, Software & Applications Conference,pp-121-126
  9. https://in.mathworks.com/discovery/simulated-annealing.html
  10. http://www.swarmintelligence.org/tutorials.php
  11. Mohammad Masdari, Farbod Salehi, Marzie Jalali, Moazam Bidaki,” A Survey of PSO-Based Scheduling Algorithms in Cloud Computing”, Journal of Network and Systems Management, Volume 25 Issue 1, January 2017, PP: 122-158,doi: 10.1007/s10922-016-9385-9
  12. Suraj Pandey, Linlin Wu, Siddeswara Mayura Guru, Rajkumar Buyya, “A Particle Swarm Optimization-based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments”, www.cloudbus.org/papers/AINA2010-PSOSched-Workflow.pdf
  13. Sajjan R.S, Biradar Rekha Yashwantrao. “Load Balancing using Cluster and Heuristic Algorithms in Cloud Domain” , Indian Journal of Science and Technology, Vol 11(15), DOI: 10.17485/ijst/2018/v11i15/118729, April 2018
  14. https://www.datascience.com/blog/k-means-clustering
  15. Surbhi Kapoor and Dr. Chetna Dabas, “Cluster Based Load Balancing in Cloud Computing”,2015 Eighth International Conference on Contemporary Computing (IC3)
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Load Balancing Heuristic Algorithms GA SA PSO