A novel architecture for data mining grid scheduler

Authors:
Meiqun Liu;Kun Gao;Zhong Wan
Affiliations:
Culture and Communication College, Zhejiang Wanli University, Ningbo, Zhejiang, P. R. China;Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, Zhejiang, P. R. China;Culture and Communication College, Zhejiang Wanli University, Ningbo, Zhejiang, P. R. China
Venue:
WSEAS TRANSACTIONS on SYSTEMS
Year:
2008

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Abstract

In order to improve the performance of Data Mining applications, an effective method is task parallelization. The scheduler on Grid plays an important role to management subtasks so as to achieve high performance. We introduce an additional component that we call serializer, whose purpose is to decompose the tasks into a series of independent tasks according the directed acyclic graph (DAG), and send them to the scheduler queue as soon as they become executable with respect to the DAG dependencies. The experimental result demonstrates that the architecture has good performance.