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Improvised Particle Swarm Optimization Technique for Workflow Balancing in Cloud

by Babita Rani Radwal, Sanjay Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 19
Year of Publication: 2018
Authors: Babita Rani Radwal, Sanjay Kumar
10.5120/ijca2018917864

Babita Rani Radwal, Sanjay Kumar . Improvised Particle Swarm Optimization Technique for Workflow Balancing in Cloud. International Journal of Computer Applications. 181, 19 ( Sep 2018), 4-9. DOI=10.5120/ijca2018917864

@article{ 10.5120/ijca2018917864,
author = { Babita Rani Radwal, Sanjay Kumar },
title = { Improvised Particle Swarm Optimization Technique for Workflow Balancing in Cloud },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2018 },
volume = { 181 },
number = { 19 },
month = { Sep },
year = { 2018 },
issn = { 0975-8887 },
pages = { 4-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number19/29969-2018917864/ },
doi = { 10.5120/ijca2018917864 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:06:22.996306+05:30
%A Babita Rani Radwal
%A Sanjay Kumar
%T Improvised Particle Swarm Optimization Technique for Workflow Balancing in Cloud
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 19
%P 4-9
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Our research focuses on improvised Particle Swam Optimization Technique for workflow balancing in cloud (IPSO-WF). The suggested technique assigns a cost to each task based on the resource requirement, the algorithm takes the four linear VMs (Virtual Machines) into deliberation before assign the job to it. The swarm searches for the VM meeting the rate, the work is assigned to the selected VM and resources updated. Since resources are allotted and VM engaged with a work the rate must needed to updated which has been disregarded in most of the research work however the planned algorithm updates the resources and rate is calculated again and again every instance when the work is assigned giving it a more realistic costing. The suggested work has been tested on 25, 50 and 75 VMs for L-ACO, B and BM. All the procedures perform best when more VMs are allotted as lesser VMs takes more resources resulting about loss of energy and time too. The acquired results shows that through all the systems are competitive but the suggested technique performs much better in the terms of time and energy.

References
  1. M. Wieczorek, R. Prodan, T. Fahringer, “Scheduling of scientific workflows in the ASKALON grid enviroment”, SIGMOD Record, vol. 34, no. 3, pp. 56–62, 2005.
  2. G. Singh, C. Kesselman, E.Deelman, “Optimizing grid-based workflow execution” , Journal of Grid Computing, vol. 3, no. 3-4, pp. 201-219, 2005.
  3. M. Xu, L. Cui, H. Wang, Y. Bi, “A multiple QoS constrained scheduling strategy of multiple workflows for cloud computing”, IEEE, 2009.
  4. S. Pandey, L. Wu, S. Guru, R. Buyya “A particle swarm optimization based heuristic for scheduling workflow applications in cloud computing environments”, pp. 400–407, IEEE, 2010.
  5. K. Liu, Y. Yang, J. Chen, X. Liu, D. Yuan, H. Jin “A Compromised-Time- Cost Scheduling Algorithm in Swin DeW-C for Instance-intensive Cost-Constrained Workflows on Cloud Computing Platform”, International Journal of High-Performance Computing Applications, vol.24 no.4 445-456,May 2008.
  6. E.-K. Byun, Y.-S. Kee, J.-S. Kim, E. Deelman, S. Maeng “Bts: Resource capacity estimate for time-targeted science workflows”, Journal of Parallel and Distributed Computing, vol. 71, no. 6, pp. 848–862, 2011
  7. S. Ghanbari, M. Othman, “A priority-based job scheduling algorithm in cloud computing”, International Conference on Advances Science and Contemporary Engineering 2012 (ICASCE ), pp.778-785, 2012.
  8. J. Durillo, H. Fard, R. Prodan “MOHEFT: A multi-objective list-based method for workflow scheduling”, pp. 185-192. IEEE, 2012.
  9. Y. Yang, X. Peng “Trust-Based Scheduling Strategy for Workflow Applications in Cloud Environment”, pp. 316-320. IEEE, 2013.
  10. Z. Wu, X. Liu, Z. Ni, D. Yuan, Y. Yang “A Market-Oriented Hierarchical Scheduling Strategy in Cloud Workflow Systems”, no. 1, pp. 256-293, Springer US 2013.
  11. Agarwal, Dr, Saloni Jain "Efficient optimal algorithm of task scheduling in cloud computing environment", arXiv preprint arXiv: 1404.2076 (2014).
  12. Li, Ji, Longhua Feng, Shenglong Fang "A greedy-based job scheduling algorithm in cloud computing", Journal of Software 9.4 (2014): 921-925.
  13. TAREGHİAN, Shahab, Zarintaj BORNAEE "A new approach for scheduling jobs in cloud computing environment", Cumhuriyet Science Journal 36.3 (2015): 2499-2506.
  14. Moganarangan, N., Babukarthik, R. G., Bhuvaneswari, S., Basha, M. S., Dhavachelvan “A novel algorithm for reducing energy consumption in cloud computing environment: Web service computing approach”, Journal of King Saud University-Computer and Information Sciences, 28(1), pp. 55-67.
  15. Chien, N. K., Son, N. H., Loc, H. D. “Load balancing algorithm based on estimating finish time of services in cloud computing”, pp. 228–233, IEEE.
  16. ZhichengCai, Xiaoping Li, Rubén Ruiz, Qianmu Li “A delay-based dynamic scheduling algorithm for bag-of-task workflows with stochastic task execution times in clouds”. Future Generation Computer Systems vol71,pp. 57–72(2017)
  17. Quanwang Wu, Fuyuki Ishikawa “Deadline-constrained Cost Optimization Approaches for Workflow Scheduling in Clouds”, IEEE, 2017
  18. Babita Rani Radwal, Sanjay Kumar “Dynamic scheduling with task completion time estimation methods in cloud”, IJCSE, Vol.6, Issue.3,March 2018
Index Terms

Computer Science
Information Sciences

Keywords

Load balancing Workflow PSO ACO

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