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Optimizing QoSin Distributed Systems / Cloud Computing Architectures

by John P. Sahlin, Shahram Sarkani, Thomas Mazzuchi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 42 - Number 18
Year of Publication: 2012
Authors: John P. Sahlin, Shahram Sarkani, Thomas Mazzuchi
10.5120/5792-8097

John P. Sahlin, Shahram Sarkani, Thomas Mazzuchi . Optimizing QoSin Distributed Systems / Cloud Computing Architectures. International Journal of Computer Applications. 42, 18 ( March 2012), 14-20. DOI=10.5120/5792-8097

@article{ 10.5120/5792-8097,
author = { John P. Sahlin, Shahram Sarkani, Thomas Mazzuchi },
title = { Optimizing QoSin Distributed Systems / Cloud Computing Architectures },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 42 },
number = { 18 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 14-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume42/number18/5792-8097/ },
doi = { 10.5120/5792-8097 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:31:38.268153+05:30
%A John P. Sahlin
%A Shahram Sarkani
%A Thomas Mazzuchi
%T Optimizing QoSin Distributed Systems / Cloud Computing Architectures
%J International Journal of Computer Applications
%@ 0975-8887
%V 42
%N 18
%P 14-20
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The primary challenge of cloud service providers is finding ways to maintain a high degree of Quality of Service (QoS) in a cost-effective manner to ensure either profitability (for business-based cloud service providers) or cost avoidance (for government cloud service providers). The traditional approach to improving system performance is to upgrade the servers and/or network backbone, an expensive undertaking. The authors used OPNET Modeler to represent distributed system architecture supporting a variety of application services and defined a framework for measuring QoS from the end-user's perspective and discovered that there is no direct relationship between server/network upgrades and overall QoS in distributed systems. This framework can be used as a decision support tool for cloud service providers to optimize the QoS of their systems by choosing upgrade strategies that provide the greatest "bang for the buck. "

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Index Terms

Computer Science
Information Sciences

Keywords

Computernetworks Quality Of Service Modeling And Simulation Computer Performance Distributed Systems

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