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Cloud Task Scheduling Based on Enhanced Meta Heuristic Optimization Technique

N. Kaur1 , C. Kathuria2 , D. Gupta3

  1. CSE, I.K.G Punjab Technical University, Kapurthala, India.
  2. CSE, I.K.G Punjab Technical University, Kapurthala, India.
  3. CSE, I.K.G Punjab Technical University, Kapurthala, India.

Correspondence should be addressed to: dineshgupta@ptu.ac.in.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-8 , Page no. 163-168, Aug-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i8.163168

Online published on Aug 30, 2017

Copyright © N. Kaur, C. Kathuria, D. Gupta . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: N. Kaur, C. Kathuria, D. Gupta, “Cloud Task Scheduling Based on Enhanced Meta Heuristic Optimization Technique,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.163-168, 2017.

MLA Style Citation: N. Kaur, C. Kathuria, D. Gupta "Cloud Task Scheduling Based on Enhanced Meta Heuristic Optimization Technique." International Journal of Computer Sciences and Engineering 5.8 (2017): 163-168.

APA Style Citation: N. Kaur, C. Kathuria, D. Gupta, (2017). Cloud Task Scheduling Based on Enhanced Meta Heuristic Optimization Technique. International Journal of Computer Sciences and Engineering, 5(8), 163-168.

BibTex Style Citation:
@article{Kaur_2017,
author = {N. Kaur, C. Kathuria, D. Gupta},
title = {Cloud Task Scheduling Based on Enhanced Meta Heuristic Optimization Technique},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2017},
volume = {5},
Issue = {8},
month = {8},
year = {2017},
issn = {2347-2693},
pages = {163-168},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1408},
doi = {https://doi.org/10.26438/ijcse/v5i8.163168}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i8.163168}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1408
TI - Cloud Task Scheduling Based on Enhanced Meta Heuristic Optimization Technique
T2 - International Journal of Computer Sciences and Engineering
AU - N. Kaur, C. Kathuria, D. Gupta
PY - 2017
DA - 2017/08/30
PB - IJCSE, Indore, INDIA
SP - 163-168
IS - 8
VL - 5
SN - 2347-2693
ER -

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Abstract

There are number of resources available for the users but user can’t afford these resources as these resources are costly. But users can use these resources on a rental basis. Internet access is readily available everywhere and it can be used by user to access the resources. So the best option available is to use the cloud service. With the growing popularity of cloud services, there come certain challenges. The problem of load balancing is its biggest challenge. Load balancing and task scheduling helps in optimizing various resource related parameters. The idea is to reduce the cost from the customer point of view and then improve the resource utilization from service provider point of view. A number of optimization algorithms have already been proposed for load balancing. This paper proposed an enhanced ACO algorithm for cloud task scheduling that helps to improve the imbalance factor of VM;s and also improve the overall Makespan time.

Key-Words / Index Term

Cloud Computing, ACO, VM, Data Center, CI, IAAS, PAAS, SAAS

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