abstract: While network problems have been addressed using a central administrative domain with a single objective, the devices in most networks are actually not owned by a single entity but by many individual entities. These entities make their decisions independently and selfishly, and maybe cooperate with a small group of other entities only when this form of coalition yields a better return. The interaction among multiple independent decision-makers necessitates the use of game theory, including economic notions related to markets and incentives. In this dissertation, we are interested in modeling, analyzing, addressing network problems caused by the selfish behavior of network entities. First, we study how the selfish behavior of network entities affects the system performance while users are competing for limited resource. For this resource allocation domain, we aim to study the selfish routing problem in networks with fair queuing on links, the relay assignment problem in cooperative networks, and the channel allocation problem in wireless networks. Another important aspect of this dissertation is the study of designing efficient mechanisms to incentivize network entities to achieve certain system objective. For this incentive mechanism domain, we aim to motivate wireless devices to serve as relays for cooperative communication, and to recruit smartphones for crowdsourcing. In addition, we apply different game theoretic approaches to problems in security and privacy domain. For this domain, we aim to analyze how a user could defend against a smart jammer, who can quickly learn about the user's transmission power. We also design mechanisms to encourage mobile phone users to participate in location privacy protection, in order to achieve k-anonymity. / Dissertation/Thesis / Ph.D. Computer Science 2013

Submitted by Erika Demachki (erikademachki@gmail.com) on 2015-02-05T19:42:01Z No. of bitstreams: 2 Dissertação - Diógenes Antonio Marques José - 2014.pdf: 9980108 bytes, checksum: eea0a39505448f7845d92bdbb4716ff2 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Erika Demachki (erikademachki@gmail.com) on 2015-02-05T19:42:44Z (GMT) No. of bitstreams: 2 Dissertação - Diógenes Antonio Marques José - 2014.pdf: 9980108 bytes, checksum: eea0a39505448f7845d92bdbb4716ff2 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2015-02-05T19:42:45Z (GMT). No. of bitstreams: 2 Dissertação - Diógenes Antonio Marques José - 2014.pdf: 9980108 bytes, checksum: eea0a39505448f7845d92bdbb4716ff2 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2014-06-05 / This work contributes with an extension to the Optimized Link State Routing protocol (OLSR) called Fuzzy Cost OLSR (OLSR-FC). In order to prevent selfish nodes as well as to improve the traffic flow over Mobile Ad-hoc Networks (MANETs), the routing metrics implemented in OLSR-FC make use of a Fuzzy Inference System (FIS) composed of 8 inference rules. Aiming at the choose of paths with low packet loss, better energy capacity and high connectivity, OLSR-FC implements a procedure of election of routes that takes into account the following parameters: Packet Loss Index (PLI), Residual Energy (RE) and Connectivity Index (CI). The OLSR-FC was evaluated by simulation through the NS- 2, in which two scenarios were implemented: a static one with 10 nodes (in testing phase), and a mobile one with up to 50 nodes. In the former scenario, a comparison was made between OLSR-FC and the original OLSR protocol which results showed that OLSR-FC overcomes OLSR in terms of throughput the packet loss. In the latter scenario, besides the original OLSR protocol, OLSR-FC was also faced up with the OLSR-ETX, OLSR-ML and OLSR-MD extensions in terms of the following performance metrics: throughput, energy consumption, packet loss rate, overhead, delay end-to-end, jitter, and packet delivery rate. In this context, results pointed that OLSR-FC achieved better performance in scenarios with a maximum of 10% of selfish nodes in comparison with every OSLR extension and the OLSR. Besides, by evaluating the main network performance metrics, such as throughput and delivery packet rate, OLSR-FC achieved eleven favorable cases against five cases in comparison with OLSR protocol. / O presente trabalho propõe uma extensão ao protocolo Optimized Link State Routing (OLSR) denominada OLSR Fuzzy Cost (OLSR-FC). A métrica de roteamento utilizada pelo OLSR-FC faz uso de um Sistema de Inferência Fuzzy (SIF), composto por 8 regras de inferência, que tem como objetivos evitar nós egoístas e melhorar o fluxo do tráfego nas redes móveis ad-hoc (MANETs). O critério de escolha de rotas leva em consideração os seguintes parâmetros: Índice de Perda de Pacotes (IPP), Energia Residual (ER) e Índice de Conectividade (IC), o propósito disso, consiste em escolher caminhos que possuam baixa perda de pacotes, melhor capacidade energética e alta conectividade. A proposta foi avaliada por simulação utilizando o simulador de redes NS-2. Foram considerados na avaliação dois cenários, um estático com 10 nós (utilizado na fase de testes) e um móvel com até 50 nós. No cenário estático o OLSR-FC foi comparado ao OLSR e os resultados mostraram que a proposta obtém vantagens com relação às métricas de desempenho vazão e perda de pacotes. No cenário móvel o OLSR-FC, além do OLSR, foi comparado às extensões OLSR-ETX, OLSR-ML e OLSR-MD, com relação as seguintes métricas de desempenho: vazão, consumo de energia, perda de pacotes, overhead, atraso fim-a-fim, jitter e taxa de entrega de pacotes. Nesse contexto, os resultados obtidos mostram que em ambientes com até 10% de nós egoístas o OLSR-FC obtém melhor desempenho que as extensões testadas e com relação ao OLSR, na mesma situação, avaliando as principais métricas de desempenho de redes, como vazão e taxa de entrega de pacotes, o OLSR-FC obteve onze casos favoráveis contra apenas cinco casos do OLSR.