Run-Time Load Balancing System on SAN-connected PC Cluster for Dynamic Injection of CPU and Disk Resource - A Case Study of Data Mining Application

Authors:
Kazuo Goda;Takayuki Tamura;Masato Oguchi;Masaru Kitsuregawa
Affiliations:
-;-;-;-
Venue:
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Year:
2002

Citing 3
Cited 1

Hash based parallel algorithms for mining association rules

DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Dynamic Load Balancing for Parallel Association Rule Mining on Heterogenous PC Cluster Systems

VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases

VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases

Towards improved load balancing for data intensive distributed computing

Proceedings of the 2011 ACM Symposium on Applied Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

PC cluster system is an attractive platform for data-intensive applications. But the conventional shared-nothing system has a limit on load balancing performance and it is difficult to change the number of nodes and disks dynamically during execution. In this paper, we develop dynamic resource injection, where the system can inject CPU power and expand I/O bandwidth by adding nodes and disks dynamically in the SAN(Storage Area Network)-connected PC cluster. Our experiments with data mining application confirm its effectiveness. We show the advantages of combining PC cluster with SAN.