Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes

This research is to propose a new efficient DNS-based load balancing algorithms that can solve a sudden increase of demand for service requests when they are applied to a local Domain Name Service (DNS) server for Web based applications and selected services. It is difficult to predict such a sud...

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Main Author:	Lu, Chin Mei
Format:	Thesis
Language:	English
Published:	2013
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://ir.unimas.my/id/eprint/9423/3/Adaptive%20System%20State%20Based%20Load%20Balancing%20For%20Web%20Application%20Server%20Cluster%20of%20Heterogeneous%20Performance%20Nodes.pdf
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id	my-unimas-ir.9423
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spelling	my-unimas-ir.94232023-03-01T09:01:33Z Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes 2013 Lu, Chin Mei QA75 Electronic computers. Computer science This research is to propose a new efficient DNS-based load balancing algorithms that can solve a sudden increase of demand for service requests when they are applied to a local Domain Name Service (DNS) server for Web based applications and selected services. It is difficult to predict such a sudden increase in traffic and service requests which is mainly due to an unbalanced distribution of workload and the unavailability of sufficient physical computing resources by the service providers. If the load balancing algorithm can accommodate computing resources of different performance level, then computing resources from various places can be temporarily placed in the server cluster to address the sudden increase in demand during peak traffic period. The proposed algorithm allows an increase in efficient load distribution among multiple Web application servers because each node may require a different level of system resources and processing power and it has the ability to adapt with the current system in a rapidly changing dynamic load environment particularly during the seasonal high traffic demand period. Finally, from the analyzed and evaluated performance results it can be deduced that the proposed ASS (Adaptive System State) DNS-based algorithms managed to improve the overall performance in term of execution time by 78.87%. This result is obtained after compared to the SPS, PI, COM, RR and lbmnaned algorithms under server cluster scenarios 1 to 6 (Table 4.3) which consists of servers with wide range of performance differences. University Malaysia Sarawak, UNIMAS 2013 Thesis http://ir.unimas.my/id/eprint/9423/ http://ir.unimas.my/id/eprint/9423/3/Adaptive%20System%20State%20Based%20Load%20Balancing%20For%20Web%20Application%20Server%20Cluster%20of%20Heterogeneous%20Performance%20Nodes.pdf text en validuser masters University Malaysia Sarawak, UNIMAS Faculty of Computer Science and Information Technology
institution	Universiti Malaysia Sarawak
collection	UNIMAS Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Lu, Chin Mei Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes
description	This research is to propose a new efficient DNS-based load balancing algorithms that can solve a sudden increase of demand for service requests when they are applied to a local Domain Name Service (DNS) server for Web based applications and selected services. It is difficult to predict such a sudden increase in traffic and service requests which is mainly due to an unbalanced distribution of workload and the unavailability of sufficient physical computing resources by the service providers. If the load balancing algorithm can accommodate computing resources of different performance level, then computing resources from various places can be temporarily placed in the server cluster to address the sudden increase in demand during peak traffic period. The proposed algorithm allows an increase in efficient load distribution among multiple Web application servers because each node may require a different level of system resources and processing power and it has the ability to adapt with the current system in a rapidly changing dynamic load environment particularly during the seasonal high traffic demand period. Finally, from the analyzed and evaluated performance results it can be deduced that the proposed ASS (Adaptive System State) DNS-based algorithms managed to improve the overall performance in term of execution time by 78.87%. This result is obtained after compared to the SPS, PI, COM, RR and lbmnaned algorithms under server cluster scenarios 1 to 6 (Table 4.3) which consists of servers with wide range of performance differences.
format	Thesis
qualification_level	Master's degree
author	Lu, Chin Mei
author_facet	Lu, Chin Mei
author_sort	Lu, Chin Mei
title	Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes
title_short	Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes
title_full	Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes
title_fullStr	Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes
title_full_unstemmed	Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes
title_sort	adaptive system state based load balancing for web application server cluster of heterogeneous performance nodes
granting_institution	University Malaysia Sarawak, UNIMAS
granting_department	Faculty of Computer Science and Information Technology
publishDate	2013
url	http://ir.unimas.my/id/eprint/9423/3/Adaptive%20System%20State%20Based%20Load%20Balancing%20For%20Web%20Application%20Server%20Cluster%20of%20Heterogeneous%20Performance%20Nodes.pdf
_version_	1783728061678616576

Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes

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