CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Evaluation of Different Virtual Machine Scheduling Algorithms in Cloud Computing Environment

by Oladoja I.P., Adewale O.S., Oluwadare S.A., Oyekanmi E.O.
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 174 - Number 32
Year of Publication: 2021
Authors: Oladoja I.P., Adewale O.S., Oluwadare S.A., Oyekanmi E.O.
10.5120/ijca2021921236

Oladoja I.P., Adewale O.S., Oluwadare S.A., Oyekanmi E.O. . Evaluation of Different Virtual Machine Scheduling Algorithms in Cloud Computing Environment. International Journal of Computer Applications. 174, 32 ( Apr 2021), 38-43. DOI=10.5120/ijca2021921236

@article{ 10.5120/ijca2021921236,
author = { Oladoja I.P., Adewale O.S., Oluwadare S.A., Oyekanmi E.O. },
title = { Evaluation of Different Virtual Machine Scheduling Algorithms in Cloud Computing Environment },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2021 },
volume = { 174 },
number = { 32 },
month = { Apr },
year = { 2021 },
issn = { 0975-8887 },
pages = { 38-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume174/number32/31887-2021921236/ },
doi = { 10.5120/ijca2021921236 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:23:43.440692+05:30
%A Oladoja I.P.
%A Adewale O.S.
%A Oluwadare S.A.
%A Oyekanmi E.O.
%T Evaluation of Different Virtual Machine Scheduling Algorithms in Cloud Computing Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 174
%N 32
%P 38-43
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Resource Scheduling is a complicated task in cloud computing, as required resources are limited and the number of users increase day by day. Thus, it is important to manage these resources in a way that they are properly utilized and the waiting time is reduced. Virtual machine (VM) scheduling algorithms are used to schedule the VM requests to the Physical Machines (PM) of a Data Center to fulfill the requirements of the requested resources. Herein, the performance efficiencies of four VM scheduling algorithms, namely: First-Come First-Serve (FCFS); Resource aware scheduling algorithm (RASA); Improved Max-Min algorithm; and Median-Based improved Max-Min were evaluated and compared using CloudSim. The Makespan, Resource utilization and Throughput calculations were used to determine the minimum makespan, maximum resource utilization, and throughput for each of the VM scheduling algorithms. The four VM scheduling algorithms were implemented, the optimization metrics were calculated, and the best algorithm was determined using the three optimization criteria. The study showed that the Median-Based improved Max-min algorithm had minimum makespan (14units time) and maximum resource utilization (2.1607) and throughput (0.714).

References
  1. Buyya R., Ranjan R., and Calheiros, R.N., (2009). “Modeling and Simulation of Scalable Cloud Computing Environments and the CloudSim Toolkit: Challenges and Opportunities”. In International Conference on High Performance Computing and Simulation (HPCS).
  2. Shamir J. (2020). “5 benefits of virtualization”. Accessed on 02-02-2021, URL: https://www.ibm.com/cloud/blog/5-benefits-of-virtualization.
  3. Liu Chen, Qiu Cai & Huang “Scheduling Parallel Jobs using Migration & Consolidation in the Cloud”, Hindwai Publications of Mathematical Problems in Engineering, July 2012.
  4. Panchal and Kapoor “Dynamic VM Allocation Algorithm using Clustering in Cloud Computing”, International Journal of Advance Research in Computer Science & Software Engineering, Issue –9, Vol. 3, September 2013 [2277 –128X.
  5. Konstantinos Psychas, and Javad Ghaderi. (2017). “On Non-Preemptive VM Scheduling in the Cloud”. Proc. ACMMeas. Anal. Comput. Syst.1, 2, Article 35 (December 2017), 29 pages. https://doi.org/10.1145/31544.
  6. Mian Guo, Quansheng Guan, and Wende KE, (2018). “Optimal Scheduling of VMs in Queueing Cloud Computing Systems with a Heterogeneous Workload”. Digital Object Identifier 10.1109/ACCESS.2018.2801319.
  7. Djouhra Dad and Ghalem Belalem,(2020).”Efficient strategies of VMs scheduling based on physicals resources and temperature thresholds”. International Journal of Cloud Applications and Computing (IJCAC) 10(3).
  8. Quiroz A, kim H, Parashar M, Gnanasambandam N, and Sharma N., (2009). Towards autonomic workload provisioning for enterprise grids and clouds. Proceedings of the 10th IEEE/ACM international conference on grid computing (grid 2009), Banf, AB, Canada,50–57.
  9. Jinhua Hu, Jianhua Gu, Guofei Sun and Tianhai Zhao, (2010). "A scheduling strategy on load balancing of virtual machine resources in cloud computing environment”. Parallel architectures, algorithms and programming (PAAP), third international symposium ,18(20),89-96.
  10. George Amalarethinam D.I. and Muthulakshmi P., (2011). “An overview of the scheduling policies and algorithms in grid computing ". International journal of research and reviews in computer science, 2(2), 280-294.
  11. I.P. Oladoja, O.S. Adewale, S.A. Oluwadare and E.O. Oyekanmi (2021). “A Threshold-based Tournament Resource Allocation in Cloud Computing Environment” Asian Journal of Research in Computer Science, Page 1-13.
  12. Er-Raji N., Benabbou F. and Eddaoui A., (2016). Task Scheduling Algorithms in the Cloud Computing Environment: Survey and Solutions. International Journal of Advanced Research in Computer Science and Software Engineering, 6(1), 604-608. 2277-128X.
  13. Bhavisha K. and Bhumi M., (2015). Review on Max-Min Task Scheduling Algorithm for Cloud Computing. Journal of Emerging Technologies and Innovative Research (JETIR), 2 (3),781-784. 2349-5162.
  14. Hoos H.H., and Stützle T., (2004). Stochastic Local Search: Foundations and Applications, Elsevier, Amsterdam, The Netherlands.
  15. Saeed P., Reza E., 2009. RASA: A New Grid Task Scheduling Algorithm", International Journal of Digital Content Technology and its applications, Vol. 3, p. 91-99.
  16. Elzeki O.M., Reshad M.Z. and Elsoud M.A. Improved Max-Min Algorithm in Cloud Computing.International Journal of Computer Applications, vol 50, No 12, July 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud simulation algorithms virtual machine scheduling cloud computing

Powered by PhDFocusTM