Desenvolvimento de um algoritmo de roteamento para redes de sensores sem fio utilizando algoritmo genético visando a eficiência energética

• Autor(a) principal: Albuquerque, Kaíque Rhuan de Azevedo
• Data de Publicação: 2020
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFPB
• Texto Completo: https://repositorio.ufpb.br/jspui/handle/123456789/18361
• topic: Rede de sensores sem fio; Nó sensor; Algoritmo de roteamento; Algoritmo genético; Balanceamento energético; Wirelles sensor network; Sensor node; Routing algorithm; Genetic algorithm; Energy balance; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA

Employed in different sectors of society, sensor nodes compose a data exchange network that helps in the reading of physical phenomena and in the control of different systems, whether making measurements or even generating control signals. Due to design limitations, in many cases these nodes have an exhaustable power source. Thus, one of the biggest problems that must be solved in the operation of a network of sensor nodes is the maintenance of the energy source. And one of the ways to carry out this maintenance is to create efficient routes for data exchange. This work presents the development of a routing algorithm for Wireless Sensor Networks (WSN). The algorithm is based on the Genetic Algorithm (AG), an optimization strategy that seeks optimal solutions to problems with techniques inspired by natural processes of evolution of species. This work presents a way to calculate valid routes between a transmitter and a receiver for delivering data packets, in addition to balancing the energy consumption of the network nodes. It is intended that there is a balanced distribution of the energy consumed in the WSN. The proposal was evaluated in a scenario of simulation of the stages of data transmission and reception in an WSN, in which the balance of energy consumption of the network nodes was assessed. This result directly affects the energy consumption by the nodes and the extension of the network’s lifetime. The results were obtained by simulation using the computational tool MATLAB® and compared with classic route mapping techniques, such as the Exhaustive Search algorithm and the Opportunistic Routing algorithm.