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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Bibliographic Details
Main Author: Lu, Chin Mei
Format: Thesis
Language:English
Published: University Malaysia Sarawak, UNIMAS 2013
Subjects:
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
http://ir.unimas.my/id/eprint/9423/
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Summary: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.