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Reseach Article

Evaluation of Auto Scaling and Load Balancing Features in Cloud

by Ashalatha R, Jayashree Agarkhed
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 6
Year of Publication: 2015
Authors: Ashalatha R, Jayashree Agarkhed
10.5120/20561-2949

Ashalatha R, Jayashree Agarkhed . Evaluation of Auto Scaling and Load Balancing Features in Cloud. International Journal of Computer Applications. 117, 6 ( May 2015), 30-33. DOI=10.5120/20561-2949

@article{ 10.5120/20561-2949,
author = { Ashalatha R, Jayashree Agarkhed },
title = { Evaluation of Auto Scaling and Load Balancing Features in Cloud },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 6 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 30-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number6/20561-2949/ },
doi = { 10.5120/20561-2949 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:58:38.781485+05:30
%A Ashalatha R
%A Jayashree Agarkhed
%T Evaluation of Auto Scaling and Load Balancing Features in Cloud
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 6
%P 30-33
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing is a latest technology that uses internet and centralized servers to maintain data and various types of applications. Cloud computing allows consumers and business people to use applications without any installation of either hardware or software and accessing their personal files at any computer with internet access. This technology allows for much more efficient computing by centralizing storage, memory, processing. The cloud computing system is the newer version of utility computing which has replaced its area at various data centers. The Load balancer determines when to start or end any virtual machine in the Cloud. The auto scaling feature along with the load balancing technique makes anyone easy to automatically increase or decrease back-end capacity to meet traffic fluctuation levels.

References
  1. Dan C. Marinescu, Cloud Computing Theory and Practice, Morgan Kaufmann, USA, Elsevier, 2013.
  2. S. K. Tesfatsion, E. Wadbro, J. Tordsson, "A combined frequency scaling and application elasticity approach for energy-efficient cloud computing," Future Generation Computer Systems 2014, pp. 205-214.
  3. Qiao hong and Yan Shoubao, "A flexible load-balancing traffic grooming algorithm in service overlay network," In proceeding of the International conference on cloud computing and big data, 2013.
  4. X. Li, Y. Mao, X. Xiao, Y. Zhuang, "An improved max-min task-scheduling algorithm for elastic cloud," In proceeding of the International symposim on computer, consumer and control, 978-1-4799-5277-9/14, IEEE 2014.
  5. P. D. Kaur, I. chana, "A resource elasticity framework for QoS aware execution of cloud applications," Future Generation Computer Systems 2014, pp. 14-25.
  6. H. Kang, J. Koh, Y. Kim, J. Hahm, "A SLA driven vm auto scaling method in hybrid cloud environment," APNOMS IEICE 2013.
  7. Y. W. Ahn, A. M. K cheng, J. Baek, M. Jo and H. chen, "An auto-scaling mechanism for virtual resources to support mobile, pervasive, real-time healthcare applications in cloud computing," 0890-8044/13, IEEE 2013.
  8. Y. Ahn, J. Choi, S. Jeong, Y. Kim, "Auto scaling method in hybrid cloud for scientific applications," IEICE – Asia-Pacific Network Operation and Management Symposium (APNOMS) 2014.
  9. Marco. A. S. Netto, C. Cardonha, R. L. F. Cunha, M. D. Assuncao, "Evaluating auto-scaling strategies for cloud computing environment," In proceeding of the 22nd International MASCOTS, 1526-7539/14, IEEE 2014.
  10. Amazon Web Services. http://aws. amazon. com/
  11. Windows Azure. http://www. windowsazure. com/
  12. Paraleap. https://www. paraleap. com
  13. L. R. Sampaio, "Towards practical auto scaling of user facing applications," LatinCloud, IEEE 2012.
  14. RightScale, http://www. rightscale. com/
  15. GoGrid, http://www. gogrid. com/
  16. Rackspace http://www. rackspace. com/
  17. Enstratus. http://www. enstratus. com/
  18. Amazon Elastic Load Balancing Developer guide 2012. http://aws. amzon. com/elb
  19. Microsoft Azure Appfabric. http://windowsazure. com/appfabric/
  20. R. Buyya, J. Broberg, A. M. Goscinski, Cloud computing: Principles and paradigms, John wiley and sons 2011.
  21. Google App Engine. http:// code. google. com/appengine/
  22. F. L. Ferraris, "Evaluating the auto scaling performance of flexiscale and amazon EC2 clouds", 14th International symposium on symbolic and numeric algorithms for scientific computing, 2012.
  23. R. Ranjan, L. Zhao, X. Wu and A. Liu, "Peer-to-Peer Cloud Provisioning: Service Discovery and Load-Balancing," http://arxiv. org/abs/0912. 1905, Dec 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud computing Auto scaling Load balancing.