A Clustering-Driven LDAP Framework

Abstract

LDAP directories have proliferated as the appropriate storage framework for various and heterogeneous data sources, operating under a wide range of applications and services. Due to the increased amount and heterogeneity of the LDAP data, there is a requirement for appropriate data organization schemes. The LPAIR & LMERGE (LP-LM) algorithm, presented in this article, is a hierarchical agglomerative structure-based clustering algorithm which can be used for the LDAP directory information tree definition. A thorough study of the algorithm’s performance is provided, which designates its efficiency. Moreover, the Relative Link as an alternative merging criterion is proposed, since as indicated by the experimentation, it can result in more balanced clusters. Finally, the LP and LM Query Engine is presented, which considering the clustering-based LDAP data organization, results in the enhancement of the LDAP server’s performance.