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Fault tolerant distributed database system via data inference

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6 Author(s)
Chu, W.W. ; Dept. of Comput. Sci., California Univ., Los Angeles, CA, USA ; Hwang, A.Y. ; Lee, R.-C. ; Chen, Q.
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A knowledge-gased approach for query processing during network partitioning is proposed. The approach uses available domain and summary knowledge to infer inaccessible data to answer a given query. A rule induction technique is used to extract correlated knowledge between attributes from the database contents. This knowledge is represented as rules for data inference. On the basis of a set of queries, simulation is used to evaluate the effectiveness of the proposed data inference technique for improving data availability under network partitioning. Object allocation has a significant impact on data availability. Allocating objects that increase remote redundancy and reduce local redundancy increases data Availability during network partitioning. A prototype distributed database system that uses the proposed inference technique with correlated knowledge from a ship database has been implemented. Experience indicates that the proposed inference technique can significantly improve the availability of a distributed database during network partitioning

Published in:

Reliable Distributed Systems, 1990. Proceedings., Ninth Symposium on

Date of Conference:

9-12 Oct 1990