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56
Provenance semirings
 PODS'07
, 2007
"... We show that relational algebra calculations for incomplete databases, probabilistic databases, bag semantics and whyprovenance are particular cases of the same general algorithms involving semirings. This further suggests a comprehensive provenance representation that uses semirings of polynomials. ..."
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Cited by 197 (30 self)
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We show that relational algebra calculations for incomplete databases, probabilistic databases, bag semantics and whyprovenance are particular cases of the same general algorithms involving semirings. This further suggests a comprehensive provenance representation that uses semirings of polynomials. We extend these considerations to datalog and semirings of formal power series. We give algorithms for datalog provenance calculation as well as datalog evaluation for incomplete and probabilistic databases. Finally, we show that for some semirings containment of conjunctive queries is the same as for standard set semantics.
Semiringbased CSPs and Valued CSPs: Frameworks, Properties, and Comparison
 Constraints
, 1999
"... In this paper we describe and compare two frameworks for constraint solving where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction, and others can be easily cast. One is based on a semiring, and the other one on a totally ordered commutative monoid. While comparing the two ..."
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Cited by 114 (27 self)
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In this paper we describe and compare two frameworks for constraint solving where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction, and others can be easily cast. One is based on a semiring, and the other one on a totally ordered commutative monoid. While comparing the two approaches, we show how to pass from one to the other one, and we discuss when this is possible. The two frameworks have been independently introduced in [2], [3] and [35].
Soft Concurrent Constraint Programming
, 2001
"... . Soft constraints extend classical constraints to represent multiple consistency levels, and thus provide a way to express preferences, fuzziness, and uncertainty. While there are many soft constraint solving algorithms, even distributed ones, by now there seems to be no concurrent programming fram ..."
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Cited by 58 (34 self)
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. Soft constraints extend classical constraints to represent multiple consistency levels, and thus provide a way to express preferences, fuzziness, and uncertainty. While there are many soft constraint solving algorithms, even distributed ones, by now there seems to be no concurrent programming framework where soft constraints can be handled. In this paper we show how the classical concurrent constraint (cc) programming framework can work with soft constraints, and we also propose an extension of cc languages which can use soft constraints to prune and direct the search for a solution. We believe that this new programming paradigm, called soft cc (scc), can be very useful in many webrelated scenarios. In fact, the language level allows web agents to express their interaction and negotiation protocols, and also to post their requests in terms of preferences, and the underlying soft constraint solver can nd an agreement among the agents even if their requests are incompatible. 1
Towards Automated Negotiation of Access Control Policies
 In Proc. of IEEE Workshop Policies for Distributed Systems and Networks
, 2003
"... We examine the problem of negotiating access control policies between autonomous domains. Our objective is to develop software agents that can automatically negotiate access control policies between autonomous domains with minimal human guidance. In this paper we show a mathematical framework that i ..."
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Cited by 22 (3 self)
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We examine the problem of negotiating access control policies between autonomous domains. Our objective is to develop software agents that can automatically negotiate access control policies between autonomous domains with minimal human guidance. In this paper we show a mathematical framework that is capable of expressing many such negotiation problems, and illustrate its application to some practical scenarios.
Soft Constraint Programming to Analysing Security Protocols
 THEORY AND PRACTICE OF LOGIC PROGRAMMING
, 2004
"... Security protocols stipulate how the remote principals of a computer network should interact in order to obtain specific security goals. The crucial goals of confidentiality and authentication may be achieved in various forms, each of different strength. Using soft (rather than crisp) constraints, w ..."
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Cited by 18 (10 self)
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Security protocols stipulate how the remote principals of a computer network should interact in order to obtain specific security goals. The crucial goals of confidentiality and authentication may be achieved in various forms, each of different strength. Using soft (rather than crisp) constraints, we develop a uniform formal notion for the two goals. They are no longer formalised as mere yes/no properties as in the existing literature, but gain an extra parameter, the security level. For example, different messages can enjoy different levels of confidentiality, or a principal can achieve different levels of authentication with different principals. The goals are formalised within a general framework for protocol analysis that is amenable to mechanisation by model checking. Following the application of the framework to analysing the asymmetric NeedhamSchroeder protocol (Bella and Bistarelli 2001; Bella and Bistarelli 2002), we have recently discovered a new attack on that protocol as a form of retaliation by principals who have been attacked previously. Having commented on that attack, we then demonstrate the framework on a bigger, largely deployed protocol consisting of three phases, Kerberos.
Semantic Optimization Techniques for Preference Queries
, 2006
"... Preference queries are relational algebra or SQL queries that contain occurrences of the winnow operator (find the most preferred tuples in a given relation). Such queries are parameterized by specific preference relations. Semantic optimization techniques make use of integrity constraints holding i ..."
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Cited by 14 (4 self)
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Preference queries are relational algebra or SQL queries that contain occurrences of the winnow operator (find the most preferred tuples in a given relation). Such queries are parameterized by specific preference relations. Semantic optimization techniques make use of integrity constraints holding in the database. In the context of semantic optimization of preference queries, we identify two fundamental properties: containment of preference relations relative to integrity constraints and satisfaction of order axioms relative to integrity constraints. We show numerous applications of those notions to preference query evaluation and optimization. As integrity constraints, we consider constraintgenerating dependencies, a class generalizing functional dependencies. We demonstrate that the problems of containment and satisfaction of order axioms can be captured as specific instances of constraintgenerating dependency entailment. This makes it possible to formulate necessary and sufficient conditions for the applicability of our techniques as constraint validity problems. We characterize the computational complexity of such problems.
Modelling Multicast QoS Routing by using BestTree Search in Andor Graphs and Soft Constraint Logic Programming
 QAPL
, 2007
"... We suggest a formal model to represent and solve the multicast routing problem in multicast networks. To attain this, we model the network adapting it to a weighted andor graph, where the weight on a connector corresponds to the cost of sending a packet on the network link modelled by that connecto ..."
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Cited by 7 (6 self)
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We suggest a formal model to represent and solve the multicast routing problem in multicast networks. To attain this, we model the network adapting it to a weighted andor graph, where the weight on a connector corresponds to the cost of sending a packet on the network link modelled by that connector. Then, we use the Soft Constraint Logic Programming (SCLP) framework as a convenient declarative programming environment in which to specify related problems. In particular, we show how the semantics of an SCLP program computes the best tree in the corresponding andor graph: this result can be adopted to find, from a given source node, the multicast distribution tree having minimum cost and reaching all the destination nodes of the multicast communication. The costs on the connectors can be described also as vectors (multidimensional costs), each component representing a different Quality of Service metric value. Therefore, the construction of the best tree may involve a set of criteria, all of which are to be optimized (multicriteria problem), e.g. maximum global bandwidth and minimum delay that can be experienced on a single link.
Confidentiality Levels and Deliberate/Indeliberate Protocol Attacks
 IN PROC. SECURITY PROTOCOLS 10TH INTERNATIONAL WORKSHOP
, 2002
"... A formal definition of confidentiality is developed using soft (rather than crisp) constraints. The goal is no longer considered as a mere yes/no property as in the existing literature, but gains an extra parameter, the security level. The higher the security level, the stronger the goal. For ex ..."
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Cited by 6 (6 self)
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A formal definition of confidentiality is developed using soft (rather than crisp) constraints. The goal is no longer considered as a mere yes/no property as in the existing literature, but gains an extra parameter, the security level. The higher the security level, the stronger the goal. For example, different messages may enjoy different levels of confidentiality, and the same message may enjoy different levels of confidentiality for different principals. On this basis, the notion of indeliberate confidentiality attack can be captured, whereby a principal learns some message not meant for him because of someone else's tampering. The analysis of Lowe's attack on the NeedhamSchroeder protocol reveals a new weakness.
Bisimulation Minimisation of Weighted Automata on Unranked Trees
, 2008
"... Two examples of automatatheoretic models for the validation of xml documents against userde ned schema are the stepwise unranked tree automaton (suta) and the parallel unranked tree automaton (puta). By adding a weight, taken from some semiring, to every transition we generalise these two qualitat ..."
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Cited by 5 (1 self)
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Two examples of automatatheoretic models for the validation of xml documents against userde ned schema are the stepwise unranked tree automaton (suta) and the parallel unranked tree automaton (puta). By adding a weight, taken from some semiring, to every transition we generalise these two qualitative automata models to quantitative models, thereby obtaining weighted stepwise unranked tree automata (wsuta) and weighted parallel unranked tree automata (wputa); the qualitative automata models are reobtained by choosing the Boolean semiring. We deal with the minimisation problem of wsuta and wputa by using (forward and backward) bisimulations and we prove the following results: (1) for every wsuta an equivalent forward (resp. backward) bisimulation minimal wsuta can be computed in time O(mn) where n is the number of states and m is the number of transitions of the given wsuta; (2) the same result is proved for wputa instead of wsuta; (3) if the semiring is additive cancellative or the Boolean semiring, then the bound can be improved to O(m log n) for both wsuta and wputa; (4) for every deterministic puta we can compute a minimal equivalent deterministic puta in time O(m log n); (5) the automata models wsuta, wputa, and weighted unranked tree automaton have the same computational power.
A Definition of Interchangeability for Soft CSPs
 In Proc. ERCIM/CologNet Workshop on Constraint  Selected Papers, LNAI
, 2002
"... Substitutability and interchangeability in constraint satisfaction problems (CSPs) have been used as a basis for search heuristics, solution adaptation and abstraction techniques. In this paper, we consider how the same concepts can be extended to soft constraint satisfaction problems (SCSPs). ..."
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Cited by 5 (4 self)
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Substitutability and interchangeability in constraint satisfaction problems (CSPs) have been used as a basis for search heuristics, solution adaptation and abstraction techniques. In this paper, we consider how the same concepts can be extended to soft constraint satisfaction problems (SCSPs).