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Real Time Resource Allocation Methodology and Quality based Framework in Cloud Computing

by Amit Kothari, Nootan Padia, Maulik Parekh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 62 - Number 11
Year of Publication: 2013
Authors: Amit Kothari, Nootan Padia, Maulik Parekh
10.5120/10126-4895

Amit Kothari, Nootan Padia, Maulik Parekh . Real Time Resource Allocation Methodology and Quality based Framework in Cloud Computing. International Journal of Computer Applications. 62, 11 ( January 2013), 31-34. DOI=10.5120/10126-4895

@article{ 10.5120/10126-4895,
author = { Amit Kothari, Nootan Padia, Maulik Parekh },
title = { Real Time Resource Allocation Methodology and Quality based Framework in Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 62 },
number = { 11 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 31-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume62/number11/10126-4895/ },
doi = { 10.5120/10126-4895 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:12:56.490684+05:30
%A Amit Kothari
%A Nootan Padia
%A Maulik Parekh
%T Real Time Resource Allocation Methodology and Quality based Framework in Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 62
%N 11
%P 31-34
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing provides resources and services as per user's demand. User can pay for these services as per their use. Many cloud users can request no. of resources or services simultaneously. So resource allocation should be cost effective, reliable and efficient. There are lots of criteria which should be considered while allocating resources to the users. This paper shows resource demand categories and requirements to be considered while allotting resources to the customer. A quality based framework is proposed in this paper.

References
  1. Daniel Warneke and Odej Kao, "Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud", IEEE transactions on parallel and distributed systems, january 2011.
  2. Venkatesa Kumar V. and S. Palaniswami, "A Dynamic Resource Allocation Method for Parallel Data Processing in Cloud Computing" Journal of computer science ,2012 Science Publications , pp. 780-788, 2012.
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  4. Chao-Tung yang, Hsiang-Yao Cheng, and Luan-Lung Huang, "A Dynamic Resource Allocation Model for Virtual Machine Management on Cloud", Grid and Distributed Computing Communications in Computer and Information Sciences, Volume 261, 2011, pp 581-590.
  5. J. G. Koomey, C. Belady, M. Patterson, A. Santos, and K. -D. Lange, "Assessing Trends over Time in Performance, Costs, and Energy Use for Servers," Intel and Microsoft, Tech. Rep. , 2009.
  6. Armbrust, M. , Fox, A. , Griffith, R. et al. Above the Clouds: A Berkeley View of Cloud Computing. UCB/EECS-2009-28, EECS Department, University of California, Berkeley, 2009.
  7. Zhikui Wang, Yuan Chen, Daniel Gmach, Sharad Singhal and Brian J. Watson, Appraise: Application-Level Performance Management in Virtualized Server Environments (Infocom) Spector, A. Z. 1989. Achieving application requirements. In Distributed Systems, S. Mullender
Index Terms

Computer Science
Information Sciences

Keywords

Cloud computing Cloud Deployment Models Cloud Services Virtual Machine Resource Allocation Resource Demand

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