W. Chu, T. Page, Q. Chen, A. Y. Hwang, O.T. Satyanarayanan
{"title":"Development of a fault tolerant distributed database via inference","authors":"W. Chu, T. Page, Q. Chen, A. Y. Hwang, O.T. Satyanarayanan","doi":"10.1109/EDS.1990.138043","DOIUrl":null,"url":null,"abstract":"The authors report on the experience of building a knowledge-based distributed database testbed on top of a commercial relational database to experiment with semantics for fault tolerance. This work sets out to test the philosophy that not only can syntactic redundancy (replication) be exploited to improve fault tolerance, but that most data are correlated, containing redundant information at the semantic level as well. The database must be engineered to make use of the inference engine to infer the inaccessible from the accessible data. The authors provide an overview of the architecture and discuss the data inference system, the knowledge schema, caching, the commercial database server, and database error handling.<<ETX>>","PeriodicalId":443013,"journal":{"name":"IEEE Workshop on Experimental Distributed Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Workshop on Experimental Distributed Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDS.1990.138043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The authors report on the experience of building a knowledge-based distributed database testbed on top of a commercial relational database to experiment with semantics for fault tolerance. This work sets out to test the philosophy that not only can syntactic redundancy (replication) be exploited to improve fault tolerance, but that most data are correlated, containing redundant information at the semantic level as well. The database must be engineered to make use of the inference engine to infer the inaccessible from the accessible data. The authors provide an overview of the architecture and discuss the data inference system, the knowledge schema, caching, the commercial database server, and database error handling.<>