Querying a Polynomial Object-Relational Constraint Database in Model-Based Diagnosis

Many papers related to Constraint Databases (CDBs) theories exist, including proposals that present frameworks for the treatment of constraints as a new data type. Our proposal presents a new way of storing and manipulating constraints as a usual data, and of making queries about the constraint variables derived from an Object-Relational Constraint Database (ORCDB). In this work, the constraints stored in an ORCDB are only polynomial equality constraints. The proposal is based on Gr¨obner bases, constraint consistency and constraint optimisation techniques. Most works in CDB use spatial-temporal data as a case study, however this work presents an emergent engineering domain, that of fault diagnosis.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

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

Developing a labelled object-relational constraint database architecture for the projection operator

Current relational databases have been developed in order to improve the handling of stored data, however, there are some types of information that have to be analysed for which no suitable tools are available. These new types of data can be represented and treated as constraints, allowing a set of data to be represented through equations, inequations and Boolean combinations of both. To this end, constraint databases were defined and some prototypes were developed. Since there are aspects that can be improved, we propose a new architecture called labelled object-relational constraint database (LORCDB). This provides more expressiveness, since the database is adapted in order to support more types of data, instead of the data having to be adapted to the database. In this paper, the projection operator of SQL is extended so that it works with linear and polynomial constraints and variables of constraints. In order to optimize query evaluation efficiency, some strategies and algorithms have been used to obtain an efficient query plan. Most work on constraint databases uses spatiotemporal data as case studies. However, this paper proposes model-based diagnosis since it is a highly potential research area, and model-based diagnosis permits more complicated queries than spatiotemporal examples. Our architecture permits the queries over constraints to be defined over different sets of variables by using symbolic substitution and elimination of variables.Ministerio de Ciencia y Tecnología DPI2006-15476-C02-0