Hierarchical classification for multiple, distributed web databases

The proliferation of online information resources increases the importance of effective and efficient distributed searching. Our research aims to provide an alternative hierarchical categorization and search capability based on a Bayesian network learning algorithm. Our proposed approach, which is grounded on automatic textual analysis of subject content of online web databases, attempts to address the database selection problem by first classifying web databases into a hierarchy of topic categories. The experimental results reported demonstrate that such a classification approach not only effectively reduces the class search space, but also helps to significantly improve the accuracy of classification performance

Distributed Model-Based Diagnosis using Object-Relational Constraint Databases

This work presents a proposal to diagnose distributed systems utilizing model-based diagnosis using distributed databases. In order to improve aspects as versatility, persistence, easy composition and efficiency in the diagnosis process we use an Object Relational Constraint Database (ORCDB). Thereby we define a distributed architecture to store the behaviour of components as constraints in a relational database to diagnose a distributed system. This work proposes an algorithm to detect which components fail when their information is distributed in several databases, and all the information is not available in a global way. It is also offered a proposal to define, in execution time, the allocation of the sensors in a distributed system.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

Heterogeneous Relational Databases for a Grid-enabled Analysis Environment

Grid based systems require a database access mechanism that can provide seamless homogeneous access to the requested data through a virtual data access system, i.e. a system which can take care of tracking the data that is stored in geographically distributed heterogeneous databases. This system should provide an integrated view of the data that is stored in the different repositories by using a virtual data access mechanism, i.e. a mechanism which can hide the heterogeneity of the backend databases from the client applications. This paper focuses on accessing data stored in disparate relational databases through a web service interface, and exploits the features of a Data Warehouse and Data Marts. We present a middleware that enables applications to access data stored in geographically distributed relational databases without being aware of their physical locations and underlying schema. A web service interface is provided to enable applications to access this middleware in a language and platform independent way. A prototype implementation was created based on Clarens [4], Unity [7] and POOL [8]. This ability to access the data stored in the distributed relational databases transparently is likely to be a very powerful one for Grid users, especially the scientific community wishing to collate and analyze data distributed over the Grid

On Dependability in Distributed Databases

Distributed database availability, reliability, and mean transaction completion time are derived for repairable database systems in which each component is continuously available for repair. Reliability is the probability that the entire transaction can execute properly without failure. It is computed as a function of mean time to failure (MTTF) and mean time to repair (MTTR). Tradeoffs between distributed database query and update are derived in terms of both performance and reliability.http://deepblue.lib.umich.edu/bitstream/2027.42/107965/1/citi-tr-92-9.pd