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In this paper we study data complexity of answering conjunctive queries over Description Logic knowledge bases constituted by an ABox and a TBox. In particular, we are interested in characterizing the FOL-reducibility and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the Description Logic used to specify the knowledge base. FOL-reducibility means that query answering can be reduced to evaluating queries over the database corresponding to the ABox. Since firstorder queries can be expressed in SQL, the importance of FOL-reducibility is that, when query answering enjoys this property, we can take advantage of Data Base Management System (DBMS) techniques for both representing data, i.e., ABox assertions, and answering queries via reformulation into SQL. What emerges from our complexity analysis is that the Description Logics of the DL-Lite family are the maximal logics allowing conjunctive query answering through standard database technology. In this sense, they are the first Description Logics specifically tailored for effective query answering over very large ABoxes.

Consider a set of parties who do not trust each other, nor the channels by which they communicate. Still, the parties wish to correctly compute some common function of their local inputs, while keeping their local data as private as possible. This, in a nutshell, is the problem of secure multiparty computation. This problem is fundamental in cryptography and in the study of distributed computations. It takes many different forms, depending on the underlying network, on the function to be computed, and on the amount of distrust the parties have in each other and in the network. We study several aspects of secure multiparty computation. We first present new definitions of this problem in various settings. Our definitions draw from previous ideas and formalizations, and incorporate aspects that were previously overlooked. Next we study the problem of dealing with adaptive adversaries. (Adaptive adversaries are adversaries that corrupt parties during the course of the computation, based on...

In this paper we formalise data models that are based on the concept of predicator, the combination of an object type and a role. A very simple model, the Predicator Model, is introduced in a rigid formal way. We introduce the concept of population as an instantiation of an information structure. A primitive manipulation language is defined in the style of relational algebra. Well-known types of constraints are defined in terms of the algebra introduced, as restrictions on populations. They are given more expressive power than is usually the case. Constraints are of central importance for identification purposes. Weak identification ensures identifiability of objects within a specific population, while structural identification ensures identifiability of objects within every population. Different levels of constraint inconsistency are defined and it is shown that the verification of two important levels is NP-complete.

We study the computational complexity of reasoning with global constraints. We show that reasoning with such constraints is intractable in general. We then demonstrate how the same tools of computational complexity can be used in the design and analysis of specific global constraints. In particular, we illustrate how computational complexity can be used to determine when a lesser level of local consistency should be enforced, when decomposing constraints will lose pruning, and when combining constraints is tractable. We also show how the same tools can be used to study symmetry breaking, meta-constraints like the cardinality constraint, and learning nogoods.

Finding solutions to a binary constraint satisfaction problem is known to be an NP-complete problem in general, but may be tractable in cases where either the set of allowed constraints or the graph structure is restricted. This paper considers restricted sets of contraints which are closed under permutation of the labels. We identify a set of constraints which gives rise to a class of tractable problems and give polynomial time algorithms for solving such problems, and for finding the equivalent minimal network. We also prove that the class of problems generated by any set of constraints not contained in this restricted set is NP-complete. 1 Introduction Finding solutions to a constraint satisfaction problem is known to be an NPcomplete problem in general [11] even when the constraints are restricted to binary constraints. However, many of the problems which arise in practice have special properties which allow them to be solved efficiently. The question of identifying restrictions t...

Finding solutions to a constraint satisfaction problem is known to be an NP-complete problem in general, but may be tractable in cases where either the set of allowed constraints or the graph structure is restricted. In this paper we identify a restricted set of contraints which gives rise to a class of tractable problems. This class generalizes the notion of a Horn formula in propositional logic to larger domain sizes. We give a polynomial time algorithm for solving such problems, and prove that the class of problems generated by any larger set of constraints is NP-complete. 1 Introduction Combinatorial problems abound in Artificial Intelligence. Examples include planning, temporal reasoning, line-drawing labelling and circuit design. The Constraint Satisfaction Problem (CSP) [14] is a generic combinatorial problem which is widely studied in the AI community because it allows all of these problems to be expressed in a natural and direct way. Reduction operations [12, 10] and intellig...

Most of today's business requirements can only be accomplished through integration of various autonomous systems which were initially designed to serve the needs of particular applications. In the literature workflows are proposed to design these kinds of applications. The key tool for designing such applications is a powerful conceptual specification language. Such a language should be capable of capturing interactions and cooperation between component tasks of workflows among others. These include sequential execution, iteration, choice, parallelism and synchronisation. The central focus of this paper is the verification of such process control aspects in conceptual workflow specifications. As it is generally agreed upon that the later in the software development process an error is detected, the more it will cost to correct it, it is of vital importance to detect errors as early as possible in the systems development process. In this paper some typical verification problems in work...

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A fault recovery system that is fast and reliable is essential to today's networks, as it can be used to minimize the impact of the fault on the operation of the network and the services it provides. This paper proposes a methodology for performing automatic protection switching (APS) in optical networks with arbitrary mesh topologies in order to protect the network from fiber link failures. All fiber links interconnecting the optical switches are assumed to be bidirectional. In the scenario considered, the layout of the protection fibers and the setup of the protection switches is implemented in nonreal time, during the setup of the network. When a fiber link fails, the connections that use that link are automatically restored and their signals are routed to their original destination using the protection fibers and protection switches. The protection process proposed is fast, distributed, and autonomous. It restores the network in real time, without relying on a central manager or a centralized database. It is also independent of the topology and the connection state of the network at the time of the failure.