An object-oriented database design for improved performance
Object-oriented databases (OODBs) are known to be rich in functionality but poor in performance. One of the important factors that affect performance is the physical database design. We developed a methodology for the design of an efficient storage structure of OODB that minimizes the database operating costs. The input for our method is the logical OODB schema and set of user transactions of retrieval and update types. The output of our method is the determination of which instance variables should be inherited from direct and indirect superclasses and stored in which subclasses. We used a genetic algorithm (GA) to solve this intractable problem. The methodology was applied on a university database. Compared to previous storage models, the storage model produced with our methodology showed database performance improvement ranging from 26% to 31%, on the average. Our results demonstrate a cost-effective storage structure design that boosts the operating performance of OODBs.
object-oriented databases physical database design database operating cost genetic algorithms performance evaluation optimization