IMPLEMENTATION AND EVALUATION OF RUNTIME DATA DECLUSTERING METHOD OVER SAN-CONNECTED PC CLUSTER

Authors

  • Masato Oguchi
  • Masaru Kitsuregawa

DOI:

https://doi.org/10.47839/ijc.1.2.123

Keywords:

Cluster Computing, Data Mining, Storage Area Network, Runtime Data Declustering

Abstract

In this paper, a PC cluster connected with Storage Area Network (SAN) is built and evaluated. In the case of SAN­connected cluster, each node can access all shared disks directly without LAN; thus, SAN­connected clusters achieve better performance than LAN­connected clusters for disk access operations. However, if a lot of nodes access the same­shared disk simultaneously, application performance degrades due to I/O­bottleneck. A runtime data declustering method, in which data is declustered to several other disks dynamically during the execution of application, is proposed to resolve this problem. Parallel data mining is implemented and evaluated on the SAN­connected PC cluster. This application requires iterative scans of a shared disk, which degrade execution performance severely due to I/O­bottleneck. The runtime data declustering method is applied to this case. According to the results of experiments, the proposed method prevents performance degradation caused by shared disk bottleneck in SAN­connected clusters.

References

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Published

2002-12-31

How to Cite

Oguchi, M., & Kitsuregawa, M. (2002). IMPLEMENTATION AND EVALUATION OF RUNTIME DATA DECLUSTERING METHOD OVER SAN-CONNECTED PC CLUSTER. International Journal of Computing, 1(2), 108-112. https://doi.org/10.47839/ijc.1.2.123

Issue

2002, Volume 1, Issue 2

Section

Articles

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