Home            Contact us            FAQs
    
      Journal Home      |      Aim & Scope     |     Author(s) Information      |      Editorial Board      |      MSP Download Statistics

     Research Journal of Applied Sciences, Engineering and Technology


A QOS Based Optimal and Cost Effective Load Balancing Strategy in Storage Cloud

1S.P. Jeno Lovesum, 2K. Krishnamoorthy and 3P. Blessed Prince
1Department of Computer Science and Engineering, Karunya University, India
2Department of Computer Science and Engineering, Sudharsan College of Engineering, India
3Department of Information Technology, Karunya University, India
Research Journal of Applied Sciences, Engineering and Technology  2014  22:4702-4705
http://dx.doi.org/10.19026/rjaset.7.854  |  © The Author(s) 2014
Received: October 25, 2013  |  Accepted: November 11, 2013  |  Published: June 10, 2014

Abstract

The aim of this paper is to create an optimal and cost effective load balancing strategy based on the QOS specified by the user which has been included as SLA in the request sent by the user to the Service provider. Cloud storage enables users to remotely store their data and enjoy the on-demand high quality cloud applications. When a user wants to store his or her files in the cloud initially they need to select a cloud service provider to use the providers storage area. Storage cloud belongs to Iaas cloud. We consider the scenario that no VM should be overloaded and at the same time no VM should be idle. For this the data file sent by the user is not stored as a whole file instead it is split into smaller files and distributed among the available VM for storage. This paper mainly focuses on QOS parameters like reliability, stability and the overall throughput.

Keywords:

Cloud, Iaas, load balancing, QOS, storage area,


References

  1. Armbrust, M., A. Fox, R. Griffith, A. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica and M. Zaharia, 2009. Above the clouds: A berkeley view of cloud computing. Technical Report No. UCB/EECS-2009-28, University of California, Berkley, USA.
  2. Beltran, M., A. Guzman and J.L. Bosque, 2011. Dealing with heteroginity in clusters. Proceeding of the 5th International Symposium on Parallel and Distributed Computing (ISPDC).
  3. Hsu, C.H. and J.W. Liu, 2010. Dynamic load balancing algorithms in homogeneous distributed system. Proceedings of the 6th International Conference on Distributed Computing Systems, pp: 216-223.
  4. Jaspreet, K., 2012. Comparison of load balancing algorithms in a Cloud. Int. J. Eng. Res. Appl., 2(3): 1169-1173.
  5. Rimal, B.P., C. Eunmi and I. Lumb, 2009. A taxonomy and survey of cloud computing systems. Proceeding of the 5th International Joint Conference on INC, IMS and IDC, pp: 44-51.
    CrossRef    
  6. Wickremasinghe, B., R.N. Calheiros and R. Buyya, 2010. CloudAnalyst: A cloudSim-based visual modeller for analysing cloud computing environments and applications. Proceeding of the 24th IEEE International Conference on Advanced Information Networking and Applications (AINA). Perth, WA, pp: 446-452.
    CrossRef    

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Information
   Sales & Services
Home   |  Contact us   |  About us   |  Privacy Policy
Copyright © 2024. MAXWELL Scientific Publication Corp., All rights reserved