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http://dx.doi.org/10.9709/JKSS.2010.19.2.081

Grid-based Biological Data Mining using Dynamic Load Balancing  

Ma, Yong-Beom (인하대학교 정보공학과)
Kim, Tae-Young (인하대학교 정보공학과)
Lee, Jong-Sik (인하대학교 정보공학과)
Publication Information
Journal of the Korea Society for Simulation / v.19, no.2, 2010 , pp. 81-89 More about this Journal
Abstract
Biological data mining has been noticed as an issue as the volume of biological data is increasing extremely. Grid technology can share and utilize computing data and resources. In this paper, we propose a hybrid system that combines biological data mining with grid technology. Especially, we propose a decision range adjustment algorithm for processing efficiency of biological data mining. We obtain a reliable data mining recognition rate automatically and rapidly through this algorithm. And communication loads and resource allocation are key issues in grid environment because the resources are geographically distributed and interacted with themselves. Therefore, we propose a dynamic load balancing algorithm and apply it to the grid-based biological data mining method. For performance evaluation, we measure average processing time, average communication time, and average resource utilization. Experimental results show that this method provides many advantages in aspects of processing time and cost.
Keywords
Dynamic load balancing; Grid computing; Biological data mining;
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