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Transactions: WSEAS TRANSACTIONS ON ELECTRONICS
Transactions ID Number: 31-863
Full Name: Kun Gao
Position: Professor
Age: ON
Sex: Female
Address: No.8 South Qian Hu Road Ningbo
Country: CHINA
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E-mail address: gaoyibo@gmail.com
Other E-mails: gaoyibo@gmail.com
Title of the Paper: High Efficient Scheduling Mechanism for Distributed Knowledge Discovery Platform
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Number of paper pages: 10
Abstract: Distributed data mining plays a crucial role in knowledge discovery in very large database. Since the distributed knowledge discovery process is both data and computational intensive, the Grid is a natural platform for deploying a high performance data mining service. The key issue for distributed data mining Grid system 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.
Keywords: Grid Computing, Data Mining, Tasks Scheduling
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