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Unicast and multicast QoS routing with softconstraint logic programming
 ACM Trans. Comput. Logic
, 2010
"... We present a formal model to represent and solve the unicast/multicast routing problem in networks with Quality of Service (QoS) requirements. To attain this, first we translate the network adapting it to a weighted graph (unicast) or andor graph (multicast), where the weight on a connector corresp ..."
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Cited by 2 (0 self)
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We present a formal model to represent and solve the unicast/multicast routing problem in networks with Quality of Service (QoS) requirements. To attain this, first we translate the network adapting it to a weighted graph (unicast) or andor graph (multicast), where the weight on a connector corresponds to the multidimensional cost of sending a packet on the related network link: each component of the weights vector represents a different QoS metric value (e.g. bandwidth, delay, packet loss). The second step consists in writing this graph as a program in Soft Constraint Logic Programming: the engine of this framework is then able to find the best paths/trees by optimizing their costs and solving the constraints imposed on them (e.g. delay ≤ 40msec), thus finding a solution to QoS routing problem. Soft constraints, and related csemiring structures,
Semiringbased soft constraints
"... Abstract. The semiringbased formalism to model soft constraint has been introduced in 1995 by Ugo Montanari and the authors of this paper. The idea was to make constraint programming more flexible and widely applicable. We also wanted to define the extension via a general formalism, so that all its ..."
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Abstract. The semiringbased formalism to model soft constraint has been introduced in 1995 by Ugo Montanari and the authors of this paper. The idea was to make constraint programming more flexible and widely applicable. We also wanted to define the extension via a general formalism, so that all its instances could inherit its properties and be easily compared. Since then, much work has been done to study, extend, and apply this formalism. This papers gives a brief summary of some of these research activities. 1 Before soft constraints: a brief introduction to constraint programming
Under consideration for publication in Theory and Practice of Logic Programming 1 The PITA System: Tabling and Answer Subsumption for Reasoning under Uncertainty
, 2003
"... Many real world domains require the representation of a measure of uncertainty. The most common such representation is probability, and the combination of probability with logic programs has given rise to the field of Probabilistic Logic Programming (PLP), leading to languages such as the Independen ..."
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Many real world domains require the representation of a measure of uncertainty. The most common such representation is probability, and the combination of probability with logic programs has given rise to the field of Probabilistic Logic Programming (PLP), leading to languages such as the IndependentChoice Logic, Logic Programs with Annotated Disjunctions (LPADs), Problog, PRISM and others. These languages share a similar distribution semantics, and methods have been devised to translate programs between these languages. The complexity of computing the probability of queries to these general PLP programs is very high due to the need to combine the probabilities of explanations that may not be exclusive. As one alternative, the PRISM system reduces the complexity of query answering by restricting the form of programs it can evaluate. As an entirely different alternative, Possibilistic Logic Programs adopt a simpler metric of uncertainty than probability. Each of these approaches – general PLP, restricted PLP, and Possibilistic Logic Programming – can be useful in different domains depending on the form of uncertainty to be represented, on the form of programs needed to model problems, and on the scale of
Semiringbased frameworks for trust . ..
"... Multitrust provides a flexible approach to encoding trust metrics whereby definitions for trust propagation and aggregation are specified in terms of a semiring. Determining the degree of trust between principals across a trust network is, in turn, programmed as a (semiring based) softconstraint sa ..."
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Multitrust provides a flexible approach to encoding trust metrics whereby definitions for trust propagation and aggregation are specified in terms of a semiring. Determining the degree of trust between principals across a trust network is, in turn, programmed as a (semiring based) softconstraint satisfaction problem. In this paper we consider the use of semiringbased metrics in reasoning about trust between coalitionforming principals. The configurable nature of multitrust makes it wellsuited to modeling trust within coalitions: whether adding more principals to a coalition increases trust or decreases trust is captured by the definition of trust aggregation within the semiring.