Self-Adaptive Databases
Abstract
The self-adaptive databases project at the University of Colorado has produced several substantial results. Parallel algorithms for the maintenance of derived data in an object-oriented database management system have been developed. These algorithms dramatically reduce the amount of I/O necessary to keep complex engineering database entities up to date. Mechanisms have been developed which integrate two directions which have been prominent in the database research community - behavioral and structural (or semantic) object- oriented modeling. This has allowed the support of data objects which are both structurally complex and behaviorally powerful. This is crucial in supporting emerging engineering applications. Also, the project has resulted in the development of mechanisms for the self-adaptive clustering of data and the self-adaptive approach is seen as a promising way to solve the well-known short-coming of relational databases - they are typically too slow to provide proper support of engineering systems. Keywords: Cactis data base management system.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 31, 1988
- Accession Number
- ADA197883
Entities
People
- Roger King
Organizations
- University of Colorado Boulder