7.4.3.3 CONSULTA MINSA Y MINAE (TERCERA ETAPA):
III. Legajo de información confidencial del expediente:
The aim of this thesis is to provide expressive means, as languages, frame- works and general aggregation schemes, in order to model and solve QoS related problems with the help of soft constraints (see Ch. 2), benefiting from Artificial Intelligence background to tackle this kind of optimization problems. Soft constraints will represent the needs of the parties on the traded resources and the consistency value of the store represents a feed- back on the current agreement. Using soft constraints gives to the service provider and the clients more flexibility in expressing their requests w.r.t. crisp constraints, and therefore there are more chances to reach a shared agreement, which is a complex task. In general, optimizing two or more metrics (e.g. bandwidth and delay) in a network is an NP-Complete prob- lem (see Ch. 4). In addition, when we have to deal with quality, many related concepts are “smooth”; for this reason, soft constraints are better than crisp constraints. Quality can be represented with intervals of “more or less” acceptable values. Moreover, the cost model is very adaptable to the specific problem, since it is parametric with the chosen semiring (see Ch. 2.2), which is an algebraic structure that can model a particular QoS feature, e.g. the availability of a service. The QoS related problems stud- ied in this work correspond to the three areas presented in this chapter: i) Networks, ii) Web Services and iii) Trust Management (TM).
This thesis is organized in this way: Chapter 1 has introduced the notion of Quality of Service and its application to three important and well known fields in Computer Science i.e. Networks, Web Services and Trust Management.
related satisfaction problems (i.e. Soft Constraint Satisfaction Problems), logic and formal languages (i.e. respectively Soft Constraint Logic Program- ming and Soft Concurrent Constraint Programming). The chapter contains the fundamental notions concerning the c-semiring algebraic structure as well.
Then, Ch. 3 defines some general algebraic frameworks to solve the Minimum Spanning Tree problem and based on c-semirings. We propose general algorithms that can compute such trees by following different cost criteria, which must be all specific instantiation of c-semirings. Our algorithms are extensions of well known procedures, as Prim or Kruskal, and show the expressivity of these algebraic structures.
In Ch. 4 we present a formal model to represent and solve the uni- cast/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 and-or 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). The second step consists in writing this graph as a program in Soft Constraint Logic Programming (SCLP): 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 problems. C-semiring structures are a convenient tool to model QoS metrics. At last, we provide an implementation of the framework over scale-free networks and we suggest how the performance can be improved.
Chapter 5 extends the Soft Concurrent Constraint Programming lan- guage in two orthogonal directions: i) we propose a timed and soft ex- tension of Concurrent Constraint Programming. The time extension is based on the hypothesis of bounded asynchrony: the computation takes a bounded period of time and is measured by a discrete global clock. Action prefixing is then considered as the syntactic marker which distinguishes a time instant from the next one. Supported by soft constraints instead of crisp ones, tell and ask agents are now equipped with a preference (or
consistency) threshold which is used to determine their success or suspen- sion. In the chapter we provide a language to describe the agents behavior, together with its operational and denotational semantics, for which we also prove the compositionality and correctness properties. Agents nego- tiating Quality of Service can benefit from this new language, by coordi- nating among themselves and mediating their preferences. Moreover, ii) we present an extension of the Soft Concurrent Constraint language that allows the nonmonotonic evolution of the constraint store. To accomplish this, we introduce some new operations: the retract(c) reduces the current store by c, the updateX(c) transactionally relaxes all the constraints of the
store that deal with the variables in the set X, and then adds a constraint c; the nask(c) tests if c is not entailed by the store. We present this frame- work as a possible solution to the management of resources (e.g. web services and network resource allocation) that need a given Quality of Service (QoS). The QoS requirements of all the parties should converge, through a negotiation process, on a formal agreement defined as the Ser- vice Level Agreement, which specifies the contract that must be enforced. c-semirings are the algebraic structures that we use to model QoS metrics. In Ch. 6 we present a variant of Datalog language (we call it DatalogW)
able to deal with weights on ground facts and to consequently compute a feedback result for the goal satisfaction. The weights are chosen from a proper c-semiring. In our context, our goal is to use this language as a semantic foundation for languages for expressing trust relationships. As a matter of fact, many of them have a semantics given in terms of crisp constraints: our approach is to extend them to cover also the soft case. Thus, we apply DatalogW as the basis to give a uniform semantics to declarative RTW(Trust Management) language family. The approach is
rather generic and could be applied to other trust management languages based on Datalog, as a semantic sublayer to represent trust management languages where the trust level is relevant.
In Ch. 7 we propose soft constraint Logic Programming based on semirings as a mean to easily represent and evaluate trust propagation in small-world networks. To attain this, we model the trust network adapting it to a weighted and-or graph, where the weight on a connector
corresponds to the trust and confidence feedback values among the con- nected nodes. Semirings are the parametric and flexible structures used to appropriately represent trust metrics. Social (and not only) networks present small-world properties: most nodes can be reached from every other by a small number of hops. These features can be exploited to reduce the computational complexity of the model. In the same model we also introduce the concept of multitrust, which is aimed at computing trust by collectively involving a group of trustees at the same time.
In Ch. 8 we represent the Optimal Stable Marriage problem as a Soft Constraint Satisfaction Problem. In addition, we extend this problem from couples of individuals to coalitions of generic agents, in order to define new coalition formation principles and stability conditions. In the coali- tion case, we suppose the preference value as a trust score, since trust can describe the belief of a node in the capabilities of another node, its honesty and reliability. Soft constraints represent a general and expres- sive framework that is able to deal with distinct concepts of optimality by only changing the related c-semiring structure, instead of using different ad-hoc algorithms. At last, we propose an implementation of the classical OSM problem by using Integer Linear Programming tools.
At last, Ch. 9 draws the final conclusions and introduces the future work with which the thesis can be extended along several and distinct directions.
Therefore, in order to link the title of this thesis (Soft Constraint Tools for Quality Aspects: Languages, Frameworks and Aggregation Schemes) to its con- tent, the “languages” are presented in Ch. 5 and Ch. 6, the “frameworks” in Ch. 3 and Ch. 4 and the “aggregation schemes” in Ch. 7 and Ch. 8.