Routing attribute data mining based on rough set theory

Authors:
Yanbing Liu;Hong Tang;Menghao Wang;Shixin Sun
Affiliations:
School of Computer Science, UEST of China, Chengdu, P. R. China;Chongqing University of Posts and Telecommunications, Chongqing, P. R. China;Chongqing University of Posts and Telecommunications, Chongqing, P. R. China;School of Computer Science, UEST of China, Chengdu, P. R. China
Venue:
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Year:
2005

Citing 2
Cited 1

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Abstract

QOSPF (Quality of Service Open Shortest Path First) based on QoS routing has been recognized as a missing piece in the evolution of QoS-based service offerings in the Internet. A data mining method for QoS routing based on rough set theory has been presented in this paper. The information system about the link is created from the subnet, and the method of rough set can mine the best route from enormous irregular link QoS data and can classify the link with the link-status data. An instance applying to the theory is presented, which verifies the feasibility that the most excellent attribute set is mined by rough set theory for compatible data table.