Submitted by Viviane Lima da Cunha (viviane@biblioteca.ufpb.br) on 2016-02-17T11:41:50Z No. of bitstreams: 1 arquivototal.pdf: 1276201 bytes, checksum: 9dd8fad80c483276a40101ee6a782d5b (MD5) / Made available in DSpace on 2016-02-17T11:41:50Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 1276201 bytes, checksum: 9dd8fad80c483276a40101ee6a782d5b (MD5) Previous issue date: 2015-07-21 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / This work deals with the p-Cluster Editing Problem (p-CEP), which consists in performing a minimum number of editions (additions or removals of edges) in a graph G in order to transform it in a disjoint union of p cliques (clusters), where G and p are input data. p-CEP is a NP-Hard problem with applications in areas such as computational biology and machine learning. To solve this problem, we propose two new mathematical formulations and improvements in a formulation from the literature, as well as new valid inequalities. The three formulations were studied both theoretically, by comparing their linear relaxations, and practically, by implementing three exact algorithms: two based on Branch-and-Cut (BC) and one based on Branch-and-Price (BP). The proposed algorithms were tested in instances with up to 211 vertices. The results show the performance of the algorithms according to the graph density and the ratio between p and the number of vertices. Overall, the BC algorithms were superior to the BP algorithm. However, the latter obtained the best dual bounds in some instances. / Este trabalho trata do Problema de Edi¸c˜ao de p-Clusters (p-PEC), o qual consiste em realizar um n´umero m´ınimo de edi¸c˜oes (adi¸c˜oes ou remo¸c˜oes de arestas) em um grafo G de modo a transform´a-lo em uma uni˜ao disjunta de p cliques (ou clusters), sendo G e p dados de entrada. O p-PEC ´e um problema NP-Dif´ıcil que possui aplica¸c˜oes em ´areas como biologia computacional e aprendizagem de m´aquina. Para resolvˆe-lo, foram propostas duas novas formula¸c˜oes matem´aticas e melhorias em uma formula¸c˜ao proveniente da literatura, bem como novas desigualdades v´alidas. As trˆes formula¸c˜oes consideradas foram estudadas tanto teoricamente, atrav´es da compara¸c˜ao entre as relaxa¸c˜oes lineares, quanto empiricamente, atrav´es do desenvolvimento de trˆes algoritmos exatos: dois baseados em Branch-and-Cut (BC) e um baseado em Branch-and-Price (BP). Os algoritmos foram testados em instˆancias com at´e 211 v´ertices. Os resultados mostram o impacto da raz˜ao entre p e o n´umero de v´ertices, da densidade do grafo e das desigualdades nos desempenhos dos algoritmos. No geral, os algoritmos BC foram superiores ao algoritmo BP. Por´em, em algumas instˆancias, os melhores limites duais foram obtidos pelo algoritmo BP.

Un des thèmes pratiques, mais hautement sensibles, est le problème de sondage dans les réseaux sociaux où le caractère secret des informations sélectionnées et la réputation de l’utilisateur sont très critiques. En effet, les utilisateurs désirent préserver la confidentialité de leurs votes et dissimuler, le cas échéant, leurs mauvais comportements. Récemment, Guerraoui et al. ont propose des protocoles de sondage basés sur la partage de secret et ne nécessitant aucune infrastructure cryptographique. Néanmoins, ces protocoles ne sont applicables que si le graphe social a une structure d’anneau et le nombre d’utilisateurs est un carré parfait. Dans cette thèse, nous traitons, d’une part, du problème du déploiement décentralisé des protocoles de sondage qui sont basés sur des graphes sociaux ayant des structures générales, et d’autre part, du problème de transformation des graphes sociaux pour augmenter les propriétés de vie privée et de précision, nécessaires au déroulement sûr et rentable du sondage décentralisé. Premièrement, nous proposons trois protocoles décentralisés qui s’appuient sur l’état originel (sans transformation) des graphes sociaux. Les deux premiers protocoles utilisent respectivement des modèles de communication synchrone et asynchrone, et manipulent des procédures de vérification pour détecter les utilisateurs malhonnêtes. Quant au troisième protocole, il est asynchrone et ne nécessite pas de procédures de vérification. Pour que ce protocole permette une diffusion efficace de messages, nous avons défini une propriété sur les graphes sociaux, appelée “m-broadcasting”. Dans la deuxième partie de la thèse, nous formalisons le problème de “l’ajout des amis” qui consiste à trouver une transformation optimale des graphes sociaux pour les adapter au partage de secret. Pour résoudre ce problème, nous présentons deux algorithmes selon deux approches différentes: centralisée et décentralisée. Une évaluation expérimentale montre que nos protocoles sont précis et restreints aux bornes théoriques / One of the current practical, useful but sensitive topic in social networks is polling problem where the privacy of exchanged information and user reputation are very critical. Indeed, users want to preserve the confidentiality of their votes and to hide, if any, their misbehaviors. Recently, Guerraoui et al. proposed polling protocols based on simple secret sharing scheme and without requiring any central authority or cryptography system. However these protocols can be deployed safely and efficiently provided that the social graph structure should be transformed into a ring structure-based overlay and the number of participating users is perfect square. In this thesis, we address the problem of deploying decentralized polling protocols for general social graphs and how to transform these graphs in order to increase the privacy and/or accuracy properties. First, we propose three simple decentralized polling protocols that rely on the current state of social graphs. The two first protocols use synchronous and asynchronous models and verification procedures to detect the misbehaving users. The third protocol is an asynchronous one that does not require any verification procedures and contains a method for efficiently broadcasting message under a family of social graphs satisfying what we call the “m-broadcasting” property. Second, we formalize the “adding friends” problem such that we can reuse the social graphs after some minimum structural modifications consisting in adding new friendship relations. We also devise algorithms for solving this problem in centralized and decentralized networks. We validate our solutions with some performance evaluations which show that our protocols are accurate, and inside the theoretical bounds