Knowledge-based approach to multiple-transaction processing and distributed data-base design
The collective processing of multiple transactions in a data-base system has recently received renewed attention due to its capability of improving the overall performance of a data-base system and its applicability to the design of knowledge-based expert systems and extensible data-base systems. This dissertation consists of two parts. The first part presents a new knowledge-based approach to the problems of processing multiple concurrent queries and distributing replicated data objects for further improvement of the overall system performance. The second part deals with distributed database design, i.e., designing horizontal fragments using a semantic knowledge, and allocating data in a distributed environment. The semantic knowledge on data such as functional dependencies and semantic-data-integrity constraints are newly exploited for the identification of subset relationships between intermediate results of query executions involving joins, such that the (intermediate) results of queries can be utilized for the efficient processing of other queries. The expertise on the collective processing of multiple transactions is embodied into the rules of a rule-based expert system, MTP (Multiple Transaction Processor). In the second part, MTP is applied for the determination of horizontal fragments exploiting the semantic knowledge. Heuristics for allocating data in local area networks are developed.
- Research Organization:
- Michigan Univ., Ann Arbor (USA)
- OSTI ID:
- 7230845
- Country of Publication:
- United States
- Language:
- English
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