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Design of QoS Architecture for Global Cloud Computing Services by Adaptive Scheduling Algorithms

by K. Ramkumar, G. Gunasekaran
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 92 - Number 8
Year of Publication: 2014
Authors: K. Ramkumar, G. Gunasekaran
10.5120/16032-5148

K. Ramkumar, G. Gunasekaran . Design of QoS Architecture for Global Cloud Computing Services by Adaptive Scheduling Algorithms. International Journal of Computer Applications. 92, 8 ( April 2014), 36-42. DOI=10.5120/16032-5148

@article{ 10.5120/16032-5148,
author = { K. Ramkumar, G. Gunasekaran },
title = { Design of QoS Architecture for Global Cloud Computing Services by Adaptive Scheduling Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 92 },
number = { 8 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 36-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume92/number8/16032-5148/ },
doi = { 10.5120/16032-5148 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:13:47.462315+05:30
%A K. Ramkumar
%A G. Gunasekaran
%T Design of QoS Architecture for Global Cloud Computing Services by Adaptive Scheduling Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 92
%N 8
%P 36-42
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper we will design architecture for cloud computing services with QoS by supported scheduling algorithm for resource allocation. Cloud generally uses virtualization technology which is specially designed for maximum resource utilization. The QoS of cloud environment for any kind of resource utilization is achieved feasibly by using QoS-aware Cache Replacement algorithm. This algorithm makes maximum utilization of resource in Cloud Environment. This accuracy is investigated by us using some measurements such as simple ping measurements which can be used as an indicator for some other QoS parameters such as jitter, throuput and delay. As a result, we were able to monitor the changes in QoS parameters during a number of days. This is also a first step towards defining QoS parameters to be included in Service Level Agreements for cloud computing in the foreseeable future.

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Index Terms

Computer Science
Information Sciences

Keywords

Adaptive scheduling Cache Replacement Algorithm QoS Resource Management

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