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

A Hierarchical Method for Dynamic Resource Allocation in Cloud

by T. R. Abinaya, P. Mathiyalagan, S. N. Sivananda
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 6
Year of Publication: 2014
Authors: T. R. Abinaya, P. Mathiyalagan, S. N. Sivananda
10.5120/15886-5063

T. R. Abinaya, P. Mathiyalagan, S. N. Sivananda . A Hierarchical Method for Dynamic Resource Allocation in Cloud. International Journal of Computer Applications. 91, 6 ( April 2014), 22-27. DOI=10.5120/15886-5063

@article{ 10.5120/15886-5063,
author = { T. R. Abinaya, P. Mathiyalagan, S. N. Sivananda },
title = { A Hierarchical Method for Dynamic Resource Allocation in Cloud },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 6 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 22-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number6/15886-5063/ },
doi = { 10.5120/15886-5063 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:12:04.234405+05:30
%A T. R. Abinaya
%A P. Mathiyalagan
%A S. N. Sivananda
%T A Hierarchical Method for Dynamic Resource Allocation in Cloud
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 6
%P 22-27
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud Computing has become a buzz word in real world. They provide rapid service to the customer mainly focusing on resource allocation. The main issue of cloud computing is to fix the dynamic resource allocation in order to improve the performance speed and reduce the cost, utilizing the resource efficiently. The main aim of this paper is resource allocation for virtualized cloud environments can improve the performance, availability, guarantees and minimize cost of the energy and time for large cloud service centers. We first formulate from virtual machine allocation for allocation main constrains are load balancing, capacity allocation, frequency scaling, energy efficiency, service differentiation for the efficient resource allocation of virtual machines in the server . Then we move to next class partitioning of incoming large tasks mainly based on weight of the task, budget and resource vector. Based on this method task are efficiently portioned and allocated to virtual machines time of completion of each task is reduced.

References
  1. Bernardetta Addis, DaniloArdagna, Barbara Panicucci, Mark S. Squillante, fellow, ieee, and li zhang ,"A Hierarchical Approach for the Resource Management of Very Large Cloud Platforms", ieee transactions on dependable and secure computing, vol. 10, no. 5, september/october 2013
  2. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Katz, A. Konwinski, G. Lee, D. A. Patterson, I. S. A. Rabkin, and M. Zaharia,"Above the Clouds: A Berkeley View of Cloud Computing," http://www. eecs. berkeley. edu/Pubs/TechRpts/2009/EECS- 2009-28. pdf, 2013.
  3. M. D. Dikaiakos, D. Katsaros, P. Mehra, G. Pallis, and A. Vakali, "Cloud Computing: Distributed Internet Computing for IT and Scientific Research," IEEE Internet Computing, vol. 13, no. 5, pp. 10- 13, Sept. /Oct. 2009.
  4. Gartner, "2012 Cloud Computing Planning Guide," http:// my. gartner. com/portal/server. pt?open=512&objID=249&mode=2&PageID=864059&resId=1837017&ref=Browse, 2013.
  5. D. Kusic, J. O. Kephart, N. Kandasamy, and G. Jiang, "Power and Performance Management of Virtualized Computing Environments via Lookahead Control," Proc. Int'l Conf. Autonomic Computing (ICAC), 2008.
  6. F. Longo, R. Ghosh, V. K. Naik, and K. S. Trivedi, "A Scalable Availability Model for Infrastructure-as-a-Service Cloud," Proc. IEEE/IFIP 41st Int'l Conf. Dependable Systems and Networks (DSN), 2011.
  7. G. S. G. E. D. Lazowska, J. Zahorjan, and K. C. Sevcik, Quantitative System Performance, Computer System Analysis Using Queueing Network Models. Prentice-Hall, 1984.
  8. H. Li and S. Venugopal, "Using Reinforcement Learning for Controlling an Elastic Web Application Hosting Platform," Proc. ACM Eighth Int'l Conf. Autonomic Computing (ICAC), 2011.
  9. Microsoft, "Windows Azure," http://msdn. microsoft. com/ en us/library/windowsazure/dd163896, 2013.
  10. C. Adam and R. Stadler, "Service Middleware for Self-Managing Large-Scale Systems," IEEE Trans. Network and Service Management, vol. 4, no. 3, pp. 50-64, Dec. 2007.
  11. J. Cao, K. Hwang, K. Li, and A. Y. Zomaya, "Optimal Multiserver Configuration for Profit Maximization in Cloud Computing," IEEE Trans. Parallel Distributed Systems, preprint, no. 99, 2012.
  12. F. Wuhib, R. Stadler, and M. Spreitzer, "A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments," IEEE Trans. Network and Service Management, vol. 9, no. 2, pp. 213- 225, June 2012.
  13. R. Raghavendra, P. Ranganathan, V. Talwar, Z. Wang, and X. Zhu, "No 'Power' Struggles: Coordinated Multi Level Power Management for the Data Center," SIGARCH Computer Architecture News, vol. 36, no. 1, pp. 48-59, 2008.
  14. S. Rivoire, P. Ranganathan, and C. Kozyrakis, "A Comparison of High-Level Full-System Power Models," Proc. Conf. Power Aware Computing and Systems (HotPower), 2008.
  15. Sheng Di, Cho-Li Wang," Dynamic Optimization OfMultiattribute Resource Allocation In Self-Organizing Clouds" IEEE Transactions On Parallel And Distributed Systems.
  16. D. Ardagna, B. Panicucci, M. Trubian, and L. Zhang, "," IEEE Trans. Services Computing, vol. 5, no. 1, pp. 2-19, Jan. -Mar. 2012.
  17. T. Nowicki, M. S. Squillante, and C. W. Wu, "Fundamentals of Dynamic Decentralized Optimization in Autonomic Computing Systems," Self-Star Properties in Complex Information Systems, pp. 204-218, Springer-Verlag, 2005.
  18. Saure D, Sheopuri A, Qu H, Jamjoom H, Zeevi A (2010)," Time-of-use pricing policies for offering cloud computing as service," in IEEE SOLI 2010, pp 300–305.
Index Terms

Computer Science
Information Sciences

Keywords

Hierarchal Framework Qos-based Load balancing and capacity Virtual system migration.

Powered by PhDFocusTM