Paper Info
Title
Collaborative Agents Supported Automatic Physical Database Design Based on Description Logics Reasoning
Abstract
Physical database design is a key phase in devising and deploying a database system to improve overall system performance, and automatic physical database design becomes an important value-added feature in a database system to decrease the TCO (total cost of ownership). A GAPDD (general automatic physical database design) framework, with two phases, the workload mining phase and the design advising phase, is provided to support automatic physical database design for relational database systems. Three collaborative agents, the workload mining agent (WMA), the feature generation agent (FGA), and the optimal search agent (OSA) work together in GAPDD. The feature generation procedure in FGA is further studied, and a reasoner based on description logics (DL) is offered to reason useful features. An index advisor for OSCAR relational engine is prototyped, and experiment results show its feasibility and efficiency
Year
DOI
Venue
2006
10.1109/CSCWD.2006.253132
CSCWD
Keywords
Field
DocType
relational database systems,workload mining agent,relational databases,automatic physical database design,general automatic physical database design,collaborative agent,inference mechanisms,collaborative agent supported gapdd,optimal search agent,feature generation agent,description logics reasoning,description logics,data mining,oscar relational engine,groupware,software agents,design advising phase,index advisor,indexation,database system,database systems,collaboration,engines,logic design,description logic,relational database system,system performance
Database tuning,Database model,Relational database,Computer science,Knowledge management,Database schema,Database design,Database testing,Physical data model,Database theory,Database
Conference
ISBN
Citations 
PageRank 
1-4244-0165-8
0
0.34
References 
Authors
4
5
Name
Order
Citations
PageRank
Tianlei Hu1309.56
Gang Chen279375.07
Yin-jie Hong300.34
Xiaolong Zhang481.13
Jinxiang Dong531165.36