CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 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

NASLA: Novel Auto Scaling Approach based on Learning Automata for Web Application in Cloud Computing Environment

by Monireh Fallah, Mostafa Ghobaei Arani, Mehrdad Maeen
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 113 - Number 2
Year of Publication: 2015
Authors: Monireh Fallah, Mostafa Ghobaei Arani, Mehrdad Maeen
10.5120/19798-1577

Monireh Fallah, Mostafa Ghobaei Arani, Mehrdad Maeen . NASLA: Novel Auto Scaling Approach based on Learning Automata for Web Application in Cloud Computing Environment. International Journal of Computer Applications. 113, 2 ( March 2015), 18-23. DOI=10.5120/19798-1577

@article{ 10.5120/19798-1577,
author = { Monireh Fallah, Mostafa Ghobaei Arani, Mehrdad Maeen },
title = { NASLA: Novel Auto Scaling Approach based on Learning Automata for Web Application in Cloud Computing Environment },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 113 },
number = { 2 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 18-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume113/number2/19798-1577/ },
doi = { 10.5120/19798-1577 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:49:55.163901+05:30
%A Monireh Fallah
%A Mostafa Ghobaei Arani
%A Mehrdad Maeen
%T NASLA: Novel Auto Scaling Approach based on Learning Automata for Web Application in Cloud Computing Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 113
%N 2
%P 18-23
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Considering the growing interest in using cloud services, the accessibility and the effective management of the required resources, irrespective of the time and place, seems to be of great importance both to the service providers and users. One of the best ways for increasing utilization and improving the performance of the cloud systems is the auto-scaling of the applications; this is because of the fact that, due to the scalability of cloud computing, on the one hand, cloud providers believe that sufficient resources have to be prepared for the users, and on the other, the users also have a tendency towards the "pay as you go" system of payment for the resources. This paper seeks to offer an approach, based on the learning automata, for the scalability of the web applications, which combines virtual machine clusters and the learning automata in order to provide the best possible way for the scaling up and scaling down of the virtual machines. The results of this study indicate that the proposed approach has decreased the number of SLA violations (in percentage), while it has a smaller load of scalability compared to the other approaches in this regard.

References
  1. Foster, Ian, Yong Zhao, Ioan Raicu, and Shiyong Lu. "Cloud computing and grid computing 360-degree compared. " In Grid Computing Environments Workshop, 2008. GCE'08, pp. 1-10. Ieee, 2008.
  2. Behnaz Seyed Taheri, Mostafa Ghobaei Arani and Mehrdad Maeen. " ACCFLA: Access Control in Cloud Federation using Learning Automata. "International Journal of Computer Applications 107(6):30-40, December 2014.
  3. Lorido-Botran, Tania, Jose Miguel-Alonso, and Jose A. Lozano. "A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments. " Journal of Grid Computing (2014): 1-34.
  4. Dutreilh, Xavier, Nicolas Rivierre, Aurélien Moreau, Jacques Malenfant, and Isis Truck. "From data center resource allocation to control theory and back. " In Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference on, pp. 410-417. IEEE, 2010.
  5. Hasan, Masum Z. , Edgar Magana, Alexander Clemm, Lew Tucker, and Sree Lakshmi D. Gudreddi. "Integrated and autonomic cloud resource scaling. " In Network Operations and Management Symposium (NOMS), 2012 IEEE, pp. 1327-1334. IEEE, 2012.
  6. Han, Rui, Li Guo, Moustafa M. Ghanem, and Yike Guo. "Lightweight resource scaling for cloud applications. " In Cluster, Cloud and Grid Computing (CCGrid), 2012 12th IEEE/ACM International Symposium on, pp. 644-651. IEEE, 2012.
  7. Chieu, Trieu C. , Ajay Mohindra, Alexei A. Karve, and Alla Segal. "Dynamic scaling of web applications in a virtualized cloud computing environment. " In e-Business Engineering, 2009. ICEBE'09. IEEE International Conference on, pp. 281-286. IEEE, 2009.
  8. Kupferman, Jonathan, Jeff Silverman, Patricio Jara, and Jeff Browne. "Scaling into the cloud. " CS270-Advanced Operating Systems (2009).
  9. Simmons, Bradley, Hamoun Ghanbari, Marin Litoiu, and Gabriel Iszlai. "Managing a SaaS application in the cloud using PaaS policy sets and a strategy-tree. " In Proceedings of the 7th International Conference on Network and Services Management, pp. 343-347. International Federation for Information Processing, 2011.
  10. RightScale. Set up Autoscaling using Voting Tags. http://support. rightscale. com/03-Tutorials/02-AWS/02-Website_Edition/Set_up_Autoscaling_using_Voting_Tags, 2012. [Online; accessed 13-September-2012].
  11. Vaquero, Luis M. , Luis Rodero-Merino, and Rajkumar Buyya. "Dynamically scaling applications in the cloud. " ACM SIGCOMM Computer Communication Review 41, no. 1 (2011): 45-52.
  12. Hung, Che-Lun, Yu-Chen Hu, and Kuan-Ching Li. "Auto-Scaling Model for Cloud Computing System. " International Journal of Hybrid Information Technology 5, no. 2 (2012).
  13. Thathachar, M. , and P. Shanti Sastry. "Varieties of learning automata: an overview. " Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on 32, no. 6 (2002): 711-722.
  14. Najim, Kaddour, and Alexander S. Poznyak. Learning automata: theory and applications. Pergamon Press, Inc. , 1994.
  15. Anari, Babak, Mohammad Reza Ahmadi, Mostafa Ghobaei Arani and Zohreh Anari. "Optimizing Risk Management Using Learning Automata. " International Journal of Computer Science Issues (IJCSI) 10, no. 3 (2013).
  16. R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. F. D. Rose, and R. Buyya, "CloudSim: A toolkit for modeling and simulation of Cloud computing environments and evaluation of resource provisioning algorithms," Software: Practice and Experience, vol. 41, no. 1, pp. 23–50, 2011.
  17. Amazon EC2 instance types, http:// aws . amazon. com/ EC2 / instance-types
Index Terms

Computer Science
Information Sciences

Keywords

Cloud computing Auto scaling Learning automata SLA violation

Powered by PhDFocusTM