NDLI: Design considerations of a fault tolerance distributed database system by inference technique

Content Provider	IEEE Xplore Digital Library
Author	Chu, W.W. Hwang, A.Y. Hecht, H. Tai, A.
Copyright Year	1990
Description	Author affiliation: Dept. of Comput. Sci., California Univ., Los Angeles, CA, USA (Chu, W.W.; Hwang, A.Y.)
Abstract	A fault-tolerant distributed database system with inference capability, consisting of a query parser and analyzer, an information module, and an inference system, is described. The information module provides the allocation and availability information of all the attributes in the system. The inference system consists of a knowledge base and an inference engine. The correlated knowledge among the attributes is represented in rules and stored in the knowledge base. During normal operations, all the database fragments are accessible; thus the processor based on the query process plan accesses the required attributes and processes the query. When network partition occurs, if the required attribute is inaccessible, the information module and the inference system will be invoked. On the basis of the required query operations provided by the parser and the correlated knowledge among the attributes, the inference engine modifies the original query to a new one so that all the required data for the query are accessible from the requested site. Depending on the type of query, the physical allocation of the database fragments, and the database domain semantics, the modified query may provide the exact, approximate, or summarized information of the original query.<>
File Size	71832
File Format	PDF
ISBN	0818620358
DOI	10.1109/PARBSE.1990.77145
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1990-03-07
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Availability Computer science Costs Weapons Fault tolerant systems Database systems Remuneration Marine vehicles Contracts Engines
Content Type	Text
Resource Type	Article

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