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A Hierarchical Method for Dynamic Resource Allocation in Cloud

by T. R. Abinaya, P. Mathiyalagan, S. N. Sivananda
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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.

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Index Terms

Computer Science
Information Sciences

Keywords

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

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