High efficient scheduler for distributed data mining applications

Authors:
Meiqun Liu;Kun Gao
Affiliations:
Culture and Communication College, Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, China;Culture and Communication College, Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, China
Venue:
CEA'09 Proceedings of the 3rd WSEAS international conference on Computer engineering and applications
Year:
2009

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Abstract

Distributed data mining plays a crucial role in knowledge discovery in very large database. The key issue for distributed data mining systems is how to scheduling data mining tasks in a high efficient way. In this paper, we propose a novel and efficient mechanism which is based on decomposing and mapping data mining tasks to DAG, and ordering them according the respective execution cost. The results show that this mechanism is scalable and feasibility.