Database buffer replacement based on network clustering and adaptive probability
HE Hong-yan
LI Guang-ming
ZHANG Hui-ping
Abstract：Aiming at the inaccurate replacement and low efficiency existing in the traditional replacement method, a large database buffer replacement method in combination with both fuzzy kohonen network clustering algorithm and adaptive probability was proposed. Through adoptingBroder theory and based on Jaccard similarity measurement, the repeated data in the buffer were eliminated, and the buffer data detection model was established. In addition, the buffer data were clustered with the fuzzykohonen clustering algorithm. The buffer features were extracted with the complex wavelet method, and the adaptive probability was introduced to replace the large database buffer. The results show that the improved buffer replacement method can effectively realize the replacement of large database buffer, increase the replacement efficiency, and enhance the overall performance of large database storage.
Keywords：large databasebufferreplacement methodimprovementfeaturenetwork clusteringadaptive probabilitydata storage
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 65-69 )