This thesis proposes different approaches to address routing and security of MANETs using swarm technology. The mobility and infrastructure-less of MANET as well as nodes misbehavior compose great challenges to routing and security protocols of such a network. The first approach addresses the problem of channel assignment in multichannel ad hoc networks with limited number of interfaces, where stable route are more preferred to be selected. The channel selection is based on link quality between the nodes. Geographical information is used with mapping algorithm in order to estimate and predict the links’ quality and routes life time, which is combined with Ant Colony Optimization (ACO) algorithm to find most stable route with high data rate. As a result, a better utilization of the channels is performed where the throughput increased up to 74% over ASAR protocol. A new smart data packet routing protocol is developed based on the River Formation Dynamics (RFD) algorithm. The RFD algorithm is a subset of swarm intelligence which mimics how rivers are created in nature. The protocol is a distributed swarm learning approach where data packets are smart enough to guide themselves through best available route in the network. The learning information is distributed throughout the nodes of the network. This information can be used and updated by successive data packets in order to maintain and find better routes. Data packets act like swarm agents (drops) where they carry their path information and update routing information without the need for backward agents. These data packets modify the routing information based on different network metrics. As a result, data packet can guide themselves through better routes. In the second approach, a hybrid ACO and RFD smart data packet routing protocol is developed where the protocol tries to find shortest path that is less congested to the destination. Simulation results show throughput improvement by 30% over AODV protocol and 13% over AntHocNet. Both delay and jitter have been improved more than 96% over AODV protocol. In order to overcome the problem of source routing introduced due to the use of the ACO algorithm, a solely RFD based distance vector protocol has been developed as a third approach. Moreover, the protocol separates reactive learned information from proactive learned information to add more reliability to data routing. To minimize the power consumption introduced due to the hybrid nature of the RFD routing protocol, a forth approach has been developed. This protocol tackles the problem of power consumption and adds packets delivery power minimization to the protocol based on RFD algorithm. Finally, a security model based on reputation and trust is added to the smart data packet protocol in order to detect misbehaving nodes. A trust system has been built based on the privilege offered by the RFD algorithm, where drops are always moving from higher altitude to lower one. Moreover, the distributed and undefined nature of the ad hoc network forces the nodes to obligate to cooperative behaviour in order not to be exposed. This system can easily and quickly detect misbehaving nodes according to altitude difference between active intermediate nodes.

Submitted by Maria Cristina (library@lncc.br) on 2016-07-27T18:14:27Z No. of bitstreams: 1 thesis andre.pdf: 6104592 bytes, checksum: 706cde4c24631f976f0ea0697eb8f078 (MD5) / Approved for entry into archive by Maria Cristina (library@lncc.br) on 2016-07-27T18:14:43Z (GMT) No. of bitstreams: 1 thesis andre.pdf: 6104592 bytes, checksum: 706cde4c24631f976f0ea0697eb8f078 (MD5) / Made available in DSpace on 2016-07-27T18:14:55Z (GMT). No. of bitstreams: 1 thesis andre.pdf: 6104592 bytes, checksum: 706cde4c24631f976f0ea0697eb8f078 (MD5) Previous issue date: 2016-05-10 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes) / Brazil has an Exclusive Economic Zone that is very extensive and rich, both in its biodiversity as in its mineral resources. In order to exploit these resources and ensure safety for navigation, Brazil must ensure its sovereignty over this part of its territory. For this purpose, Brazil has the Naval Power exercised by the Brazilian Navy. Among the operations carried out by the Navy there are the search and reconnaissance missions, carried out by ships and by naval aircraft. This work is focused on reconnaissance missions carried out by naval aircraft. The main objective is the evaluation of meta-heuristics for the development of an application that can generate optimized routes for aircraft in the missions, attending the requirements of the Brazilian Navy. This work presents the methods developed based on two nature inspired meta-heuristics, for the elaboration of optimized routes for aircraft. The method is complying with two main constraints for these missions: checkpoints (targets) mobility and the limit of aircraft autonomy. It also presents the results of tests performed with the methods developed in this work and a general evaluation of their performance. / O Brasil possui uma área de Zona Econômica Exclusiva muito extensa e muito rica, tanto na sua biodiversidade como em recursos minerais. Porém, para poder explorar estas riquezas e garantir a segurança para a navegação destas águas o Brasil precisa assegurar sua soberania sobre esta parte de seu território. Para isso conta com o Poder Naval exercido pela Marinha do Brasil, que entre as operações por ela realizadas estão as missões de busca e esclarecimento, tanto por embarcações, como por aeronaves embarcadas. Este trabalho tem seu foco nas operações de esclarecimento por aeronaves embarcadas, tendo como objetivo principal a avaliação de meta-heurísticas para a elaboração de uma aplicação capaz de gerar rotas otimizadas para as aeronaves, em missões de esclarecimento, as quais atendam as necessidades da Marinha do Brasil. Neste trabalho, são apresentados os métodos desenvolvidos com base em duas meta-heurísticas, baseadas na natureza, para a elaboração de rotas otimizadas para as aeronaves, atendendo a duas restrições fundamentais em missões de esclarecimento aéreo, a mobilidade dos pontos de checagem (alvos) e o limite de autonomia das aeronaves. Também são apresentados os resultados dos testes realizados com os métodos desenvolvidos e uma avaliação geral dos seus desempenhos.

This diploma thesis deals with the path planning by swarm intelligence. In the theoretical part it describes the best known methods of swarm intelligence (Ant Colony Optimization, Bee Swarm Optimization, Firefly Swarm Optimization and Particle Swarm Optimization) and their application for path planning. In the practical part particle swarm optimization is selected for the design and implementation of path planning in the C#.