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

Applying Constraint Databases in the Determination of Potential Minimal Conflicts to Polynomial Model-Based Diagnosis

Model-based Diagnosis allows the identification of the parts which fail in a system. The models are based on the knowledge of the system to diagnose, and may be represented by constraints associated to the components. The variables of these constraints can be observable or non-observable, depending on the situation of the sensors. In order to obtain the potential minimal diagnosis in a system, an important issue is related to finding out the potential minimal conflicts in an efficient way. We consider that Constraint Databases represent an excellent option in order to solve this problem in complex systems. In this work we have used a novel logical architecture of Constraint Databases which has allowed obtaining these potential conflicts by means of the corresponding queries. Moreover, we have considered Gröbner Bases as a projection operator to obtain the potential minimal conflicts of a system. The first results obtained on this work, which are shown in a heat exchangers example, have been very promising.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

An Open-Source Proactive Security Infrastructure for Business Process Management

Business Process Management Systems (BPMS) have emerged in the IT arena as cornerstone in the automation and orchestration of complex services for organizations. These systems manage critical information that is crucial for the organizations. The potential cost and consequences of security threats could produce information loss for the reputation of organizations. Therefore, the early response regarding to the non-compliance of security requirement is a real necessity overall during the business process execution. Currently, an active response requires a human intervention with high know-how and expertise in both business process management and security. In this paper, we propose an initial work which presents an open-source proactive infrastructure for the automatic continuous monitoring and checking compliance of security requirements at runtime of business processes

A survey using constraints to decision-making for fault tolerance in Business processes

Sometimes the business processes do not work how it is expected. In these cases, a diagnosis process has to be executed to determine the responsible activity or activities of the fault in order to substitute it or them for a correct activity. The aim of this paper is describe the necessary steps to find out another service that can replace it in an efficient way. In order to automate the search and substitution of activities, we propose to describe the functionality of the tasks using constraints, making easier the determination of the possible activities that could substitute everyone faulty activities in the business process. In this paper, it is also analyzed how to adapt the communication protocol with XML messages to a behavior described using constraints.Junta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-1371

Determination of Possible Minimal Conflict Sets Using Constraint Databases Technology and Clustering

Model-based Diagnosis allows the identification of the parts which fail in a system. The models are based on the knowledge of the system to diagnose, and can be represented by constraints associated to components. Inputs and outputs of components are represented as variables of those constraints, and they can be observable and non-observable depending on the situation of sensors. In order to obtain the minimal diagnosis in a system, an important issue is to find out the possible minimal conflicts in an efficient way. In this work, we propose a new approach to automate and to improve the determination of possible minimal conflict sets. This approach has two phases. In the first phase, we determine components clusters in the system in order to reduce drastically the number of contexts to consider. In the second phase, we construct a reduced context network with the possible minimal conflicts. In this phase we use Gröbner bases reduction.A novel logical architecture of Constraint Databases is used to store the model, the components clusters and possible minimal conflict sets. The necessary information in each phase is obtained by using a standard query language.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

Constraint Databases Technology for Polynomial Models Diagnosis

Model-based Diagnosis allows the identification of the parts which fail in a system. The models are based on the knowledge of the system to diagnose, and they can be represented by constraints associated to the components. The variables including in these con straints can be observable or non-observable, depending on the situa tion of sensors. In order to obtain the minimal diagnosis in a system, an important issue is related to find out the minimal possible conflicts in an efficient way. We consider that Constraint Databases represent an excellent approach in order to solve this problem in complex sys tems, where a tuple in a relational database could be replaced by a conjunction of constraints. In this work we have used a novel logical architecture of Con straint Databases which has allowed us to obtain these possible min imal conflicts by means of a standard query language though the in formation is stored in a conventional relational database. Moreover, we have considered Grobner bases as a projection operator to obtain ¨ the minimal possible conflicts of a system.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

Run-Time Auditing for Business Processes Data Using Constraints

Business processes involve data that can be modified or up dated by various activities. These data must satisfy the business rules associated to the process. These data are normally stored in a rela tional database, and hence the database has to be analyzed to determine whether the business rules can be satisfied. This paper presents a framework including a run-time auditing layer where the correctness of a database can be analyzed at different check points of a business process according to the data flow. It provides an early detection of incorrect action on stored data. Furthermore, in or der to manage the current business rules, the use of the constraint pro gramming paradigm is proposed and the enlargement of the Constraint Database Management Systems to support business rulesJunta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-1371

Model-Driven Engineering for Constraint Database Query Evaluation

Data used in applications such as CAD, CAM or GIS are complex, but the techniques developed for their treatment and stor age are not adapted enough to their needs. Examples of these types of data are spatiotemporal, scientific, economic or industrial information, in which data has not a single value because is defined by parameters, variables, functions, equations . . .. These complex data cannot be repre sented nor evaluated with the relational algebra types, then a new, more complex, data type is needed, the Constraint type. Constraint Databases were defined and implemented in order to handle this type of constraint data. When a Constraint Database is implemented, different configura tion parameters can be set up, depending on which database manager is going to be used, which constraint programming tool is going to solve the query evaluation, or which type of constraints can be involved. When some of these parameters are changed, the implementation that supports the evaluation of queries over constraints have to be changed too. For this reason, we propose the use of Model-Driven Engineering to model the queries over Constraint Databases in an independent way of the im plementation and the techniques used to evaluate the queries.Junta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-13714Ministerio de Ciencia y Tecnología TIN2010- 21744-C02-0

FABIOLA: Defining the Components for Constraint Optimization Problems in Big Data Environment

The optimization problems can be found in several examples within companies, such as the minimization of the production costs, the faults produced, or the maximization of customer loyalty. The resolution of them is a challenge that entails an extra effort. In addition, many of today’s enterprises are encountering the Big Data problems added to these optimization problems. Unfortunately, to tackle this challenge by medium and small companies is extremely difficult or even impossible. In this paper, we propose a framework that isolates companies from how the optimization problems are solved. More specifically, we solve optimization problems where the data is heterogeneous, distributed and of a huge volume. FABIOLA (FAst BIg cOstraint LAb) framework enables to describe the distributed and structured data used in optimization problems that can be parallelized (the variables are not shared between the various optimization problems), and obtains a solution using Constraint Programming Techniques

Fault diagnosis in databases for business processes

Business processes involve data that can be modified or updated by various activities. These data must satisfy the business rules associated to the process. As the information treated in a business process tends to be extensive, data are normally stored in a relational database, and hence the database has to be analyzed to determine whether the business rules are satisfied and what values are incorrect. This paper proposes the use of model-based diagnosis in the business processes scenario. This scenario combines business processes, business rules, relational databases and where the faults are the instances of the variables introduced by the users. These considerations make it necessary to introduce a new way for representing the model, and the design of new algorithms to solve it. This model provides a means for the detection of incorrect tuples of different tables of the database by avoiding the analysis of the full database. Furthermore, in order to manage the current business rules, the use of a constraint paradigm is proposed and by using Max- CSPs to isolate incorrect values.Junta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-1371