CFP last date
20 December 2024
Reseach Article

Utilizing AHP: Resource Allocation Problem in Cloud

by Avtar Singh, Kamlesh Dutta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 128 - Number 15
Year of Publication: 2015
Authors: Avtar Singh, Kamlesh Dutta
10.5120/ijca2015906409

Avtar Singh, Kamlesh Dutta . Utilizing AHP: Resource Allocation Problem in Cloud. International Journal of Computer Applications. 128, 15 ( October 2015), 33-37. DOI=10.5120/ijca2015906409

@article{ 10.5120/ijca2015906409,
author = { Avtar Singh, Kamlesh Dutta },
title = { Utilizing AHP: Resource Allocation Problem in Cloud },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 128 },
number = { 15 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 33-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume128/number15/22951-2015906409/ },
doi = { 10.5120/ijca2015906409 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:21:48.059177+05:30
%A Avtar Singh
%A Kamlesh Dutta
%T Utilizing AHP: Resource Allocation Problem in Cloud
%J International Journal of Computer Applications
%@ 0975-8887
%V 128
%N 15
%P 33-37
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud Computing is changing the scheme by providing different services to business and government sectors as well as to sole users irrespective of their location. Cloud Computing provides scalable and on demand services to users, but this technology has many challenges. In several applications the last decision is based on the estimate of a number of alternatives in terms of a number of criteria. This problem may become difficult one when criteria are expressed in different tasks or jobs, relevant data are difficult to be quantified. The Analytic Hierarchy Process (AHP) is an effective method dealing with this kind of decision problems. This paper deals with priorities, ranking with consistency method and their results are given through a numerical example. The results show that distributive mode has fast convergence and smaller computational complexity than ideal mode for close system when the AHP method is used in cloud computing applications.

References
  1. Hayes Brain. (2008) Cloud computing. Commun ACM, 51(7):9–11.
  2. Mell P., Grance T. (2011) The NIST definition of cloud computing. Special Publication, 2011, pp. 800-145.
  3. Buyya R, Yeo C.S., Srikumar V, James B, Ivona B. (2009) Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener Comput Syst, 2009, 25(6):599–616.
  4. Armbrust M., Fox A., Griffith R., Joseph A., Katz R., Konwinski A. … Zaharia M. (2009) Above the clouds: A Berkeley view of cloud computing. Technical Report, University of California at Berkeley.
  5. Chieu T. C., Mohindra A., Alexei A., Karve A.A., Segal A.A.(2009) Dynamic scaling of web applications in a virtualized cloud computing environment. In Proceedings of the IEEE International Conference on e-Business Engineering, pp.281–286.
  6. Buyya R., Broberg J., Goscinski A. (2011) Cloud computing: Principle and paradigm. John Wiley& Sons.
  7. Martens, B., and Teuteberg, F. (2012) Decision-making in cloud computing environments: a cost and risk based approach. Information Systems Frontiers, 14, 4:871–893.
  8. Ergu D, Kou G, Peng Y, Shi Y, Shi Y. (2011) The analytic hierarchy process: task scheduling and resource allocation in cloud computing environment, J. Supercomput. Springer ScienceBusiness Media, pp. 835-848.
  9. Saaty TL. (2009) A scaling method for priorities in hierarchical structures. J of Mathematical Psychology, 1977, pp. 234-281.
  10. Saaty TL. (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res, 48(1): 9–26.
  11. Saaty TL. (2003) Decision-making with the AHP: Why is the principal eigenvector necessary. Eur J Oper Res, 145:85-89.
  12. Brijesh Deb. (2010) Assess enterprise applications for cloud migration Using the Analytic Hierarchy Process to evaluate apps for the cloud, white paper IBM Corporation, pp.1-11.
  13. Srdjevic B. (2005) Combining different prioritization methods in the analytic hierarchy process synthesis. Computers & Operations Research, pp. 1897–1919.
  14. Godse, M. and Mulik, S. (2009) An approach for selecting Software-as a- Service (SaaS) product. In Proceedings of the IEEE International Conference on Cloud Computing, pp. 155–158.
  15. Singh A, Dutta K., Singh A. (2014) Resource allocation in cloud computing environment using AHP technique. International journal of cloud Applications and Computing, 4(1): 33-44.
  16. Li C, Li H, Sun Y, Jia Y. (2008) An Improved Ranking Approach to AHP Alternatives Based on Variable Weights, Intelligent Control and Automation, pp. 8255-8260.
  17. Carlucci D, Schiuma G. (2007) Knowledge assets value creation map assessing knowledge assets value drivers using AHP. Expert Systems with Applications, 32: 814-821.
  18. Rao R.V. (2013) Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods, Springer Series in Advanced Manufacturing, Verlag London: 2013.
  19. Triantaphyllou E, Mann S.H. (1995) Using the analytic hierarchy process for decision making in engineering applications: some challenges. Inter’l Journal of Industrial Engineering: Applications and Practice, 2(1): 35-44.
  20. Gao S, Zhang Z, Cao C. New Methods of Estimating Weights in AHP, Proceedings of the International Symposium on Information Processing, 2009, pp.201-204.
  21. Millet, I., Saaty, T. On the relativity of relative measures-accommodating both rank preservation and rank reversals in the AHP. European Journal of Operational Research, 2000, 121(1): 205–212.
  22. Ishizaka, A., Labib, A. (2009) Analytic Hierarchy Process and Expert Choice: Benefits and limitations. Operational Research Society. 2009; 22, 4:201–220.
Index Terms

Computer Science
Information Sciences

Keywords

Analytic Hierarchy Process pairwise comparison matrix Priority vector Consistency index