this paper, we present an access control model in which periodic temporal intervals are associated with authorizations. An authorization is automatically granted in the specified intervals and revoked when such intervals expire. Deductive temporal rules with periodicity and order constraints are provided to derive new authorizations based on the presence or absence of other authorizations in specific periods of time. We provide a solution to the problem of ensuring the uniqueness of the global set of valid authorizations derivable at each instant, and we propose an algorithm to compute this set. Moreover, we address issues related to the efficiency of access control by adopting a materialization approach. The resulting model provides a high degree of flexibility and supports the specification of several protection requirements that cannot be expressed in traditional access control models.

This paper introduces a generalization of Datalog based on the notion of integer periodicity constraints. A closed form evaluation procedure running in PTIME for this class of constraints is developed. The periodicity constraints are then combined with integer (gap-)order constraints and an evaluation procedure for the combination is developed. A general method for combining different classes of constraints in the framework of Datalog is also discussed. 1 Introduction Generalized databases [1, 10, 12] are infinite databases that can be represented using finite sets of generalized (or constraint) tuples. A number of query languages over such databases have been studied. The proposed query languages differ with respect to: ffl the underlying inference mechanism (first order vs. deductive) ffl the constraint language used. In this paper we study generalized Datalog programs (function-free logic programs) that operate on constraint tuples in the place of ground atoms. This idea comes fr...

. Constraint databases generalize relational databases by finitely representable infinite relations. This paper surveys the state of the art in constraint databases: known results, remaining open problems and current research directions. The paper also describes a new algebra for databases with integer order constraints and a complexity analysis of evaluating queries in this algebra. In memory of Paris C. Kanellakis 1 Introduction There is a growing interest in recent years among database researchers in constraint databases, which are a generalization of relational databases by finitely representable infinite relations. Constraint databases are parametrized by the type of constraint domains and constraint used. The good news is that for many parameters constraint databases leave intact most of the fundamental assumptions of the relational database framework proposed by Codd. In particular, 1. Constraint databases can be queried by constraint query languages that (a) have a semantics ba...

In previous work we have developed the scheme of indefinite L-constraint databases where L, the parameter, is a first-order constraint language. This scheme extends the constraint database proposal of Kanellakis, Kuper and Revesz to include indefinite (or uncertain) information in the style of Imielinski and Lipski. In this paper we study the complexity of query evaluation in an important instance of this abstract scheme: indefinite temporal constraint databases. Our results indicate that the data/combined complexity of query evaluation does not change when we move from queries in relational calculus over relational databases, to queries in relational calculus with temporal constraints over temporal constraint databases. This fact remains true even when we consider query evaluation in relational databases with indefinite information vs. query evaluation in indefinite temporal constraint databases. In the course of our work, we provide precise bounds on the complexity of decision/quanti...

Abstract. Extension of the relational database model to represent complex data has been a focus of much research in recent years. At the same time, an alternative extension of the relational database model has proposed using constraint databases that finitely describe infinite relations. This paper attempts to combine these two divergent approaches. In particular a query language called Datalog with set order constraints, or Datalog ⊂ P(Z) , is proposed. This language can express many natural problems with sets, including reasoning about inheritance hierarchies. Datalog ⊂ P(Z) queries over set constraint databases are shown to be evaluable bottom-up in closed form and to have DEXPTIME-complete data complexity. 1

. Guaranteeing termination of programs on all valid inputs is important for database applications. Termination cannot be guaranteed in Stratified Datalog with integer (gap)-order, or Datalog :;! Z , programs on generalized databases because they can express any Turingcomputable function [23]. This paper introduces a restriction of Datalog :;! Z that can express only computable queries. The restricted language has a high expressive power and a non-elementary data complexity. 1 Introduction Constraint logic programming [14, 15, 27, 12, 10, 9] has a great potential for being adapted for database use. A successful adaptation of constraint logic programming has to meet usual database requirements. In the constraint query languages framework [19] two requirements are identified as especially important: (a) closed-form evaluation and (b) bottom-up processing. Closed-form evaluation means that all possible tuple answers to a query are represented finitely by an output constraint database ...

. This paper describes the implementation of a constraint database system with integer and set of integers data types. The system called DISCO allows Datalog queries and input databases with both integer gap-order [30] and set order constraints [31]. The DISCO query language can easily express many complex problems involving sets. The paper also presents efficient running times for several sample queries. 1 Introduction Recently there has been much interest in constraint databases that generalize relational databases by allowing infinite relations that are finitely represented using constraint tuples (ex., [23, 3, 4, 8, 17, 21, 25, 28]). DISCO (short for Datalog with Integer and Set order COnstraints) is a constraint database system being developed at the University of Nebraska. DISCO implements a particular case of constraint query languages for which a general framework was proposed in [23] analogously to the constraint logic programming framework of Jaffar and Lassez [18]. The part...

We consider the data complexity of various logics on two important classes of constraint databases: dense order and linear constraint databases. For dense order databases, we present a general result allowing us to lift results on logics capturing complexity classes from the class of finite ordered databases to dense order constraint databases. Considering linear constraints, we show that there is a significant gap between the data complexity of first-order queries on linear constraint databases over the real and the natural numbers. This is done by proving that for arbitrary high levels of the Presburger arithmetic there are complete first-order queries on databases over (N; !; +). The proof of the theorem demonstrates a simple argument for translating complexity results for prefix classes in logical theories to results on the complexity of query evaluation in constraint databases.

. In this paper we consider Datalog queries with linear constraints. We identify several syntactical subcases of Datalog queries with linear constraints, called safe queries, and show that the least model of safe Datalog queries with linear constraints can be evaluated bottomup in closed-form. These subcases include Datalog with only positive and upper-bound or only negative and lower bound constraints or only half-addition, upper and lower bound constraints. We also study other subcases where the recognition problem is decidable. 1 Introduction Constraint databases is an active area of current research. In particular, linear constraint databases have been used for modeling geometric data and in other applications [3, 14, 15, 22, 23]. There are several proposals to define query languages for linear constraint databases. Most query language proposals are based on first-order logic. However, it has been found that first-order languages even with real polynomial constraint databases are ...

This paper proposes an efficient method for evaluating queries over constraint databases. The method is based on a combination of top-down resolution with memoing and closed form bottom-up evaluation. In this way top-down evaluation terminates for all queries for which the bottom-up evaluation also terminates. The main advantage of the proposed method is the direct use of partially instantiated queries without the need for rewriting of the original program. The evaluation algorithm automatically propagates the necessary constraints during the computation. In addition, top-down evaluation potentially allows the use of compilation techniques developed for compilers of logic programming languages, which can make query evaluation very efficient. 1 Introduction We propose a new method for evaluating deductive queries over constraint databases (i.e., where the constraints are used to represent the information stored in generalized relations [7]). The evaluation of queries in constraint dat...