S. Bing Yao

FORMANAGER: an office forms management system

The form has become an important abstraction for data management in an office application environment. Structured office forms present data to users in an easily understood and easily manipulated manner. In this paper we classify forms systems in terms of three dimensions: data structuring, user interfaces, and programming interfaces. Current forms systems are analyzed under these dimensions. We have designed a comprehensive forms management system, FORMANAGER, that includes facilities for form specification, form processing, and form control. The system transforms data from a relational database into a hierarchical data structure which defines the form. The design and algorithms for implementation of the system are described, and future extensions to enhance the capabilities of forms systems are proposed.

Requirements-driven database systems benchmark method

Benchmarks are the vital tools in the performance measurement, evaluation, and comparison of relational database management systems (RDBMS). Standard benchmarks such as the TP1, TPC-A, TPC-B, TPC-C, TPC-D, TPC-H, TPC-R, TPC-W, Wisconsin, and AS3 Ap benchmarks have been used to assess the performance of relational database management systems. These benchmarks are synthetic and domain-specific. Test results from these benchmarks are estimates of possible system performance for certain pre-determined application types. Database system performance on actual database domain may vary significantly from those in the standard benchmarks. In this paper, we describe a new benchmark method that is computer-assisted and developed from the perspective of the users requirements.

An iterative method for distributed database optimization

Abstract The development of a distributed database system requires effective solutions to many complex and interrelated design optimization problems. The cost dependencies between query optimization and data allocation on distributed systems are well recognized but little understood. We investigate these dependencies by proposing and analysing an iterative heuristic which provides an integrated solution to the query optimization and data allocation problems. The optimization heuristic iterates between finding minimum-cost query strategies and minimum-cost data allocations until a local minimum for the combined problem is found. A search from convergence efficiently scans the optimization search space for lower-cost solutions. In this paper, we apply the iterative heuristic to a realistic distributed database system model and a general class of queries and obtain very significant performance benefits. Experimental results demonstrate clear improvements in performance for the iterative method over existing design methods in a general-query environment. The iterative heuristic is proposed as a framework for future research extensions to achieve distributed system optimization.