Modelo de otimização multiobjetivo para roteamento em redes sem fio

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2017-09-01

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Universidade Federal de Goiás

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Owing to the huge range of application scenarios for wireless networks, new prospects for the current and future applications of the Internet, making new communication paradigms such as the Internet of Things (IoT) and 5G networks. Two important networks are included in this scenery: Wireless Sensor Networks (WSN) provide key devices for developing the IoT communication paradigm, such as the sensors used for collecting different kind of information, and the Wireless Mesh Network (WMN) that enable interoperability between heterogeneous network, covering large areas with at am low cost.Eeach one these networks have specific characteristics, for example, the WSN has serious restrictions (e.g. power consumption, low speed wireless links, interference) while the WMN offers high data rates through multiple radios and channels. In this context, it is necessary to find solutions that can ensure more efficient communication system based on the optimized utilization of the network resources. So it was created a multi-objective routing algorithm, called Routing-Aware of path Length, Link quality, and traffic Load (RALL). This seeks to strike a balance between three objectives: to minimize the network bottlenecks, to reduce path length, and to avoid links with low quality, for resolution the routing problem for WSN, Then the RALL approach was adapted to match the specialty of the WMN, entitled Routing Aware of path Length, Link quality, and traffic Load Weighted (RALLW). The results indicate that combining multiple objectives when performing routing can benefit networks performance. The RALL and RALLW results in a good performance with regard to the delivery rate, throughput, delay, and power consumption when compared to other approaches, however the RALLW approach did not significant differences when compared to the RALL.

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MEDEIROS, Vinícius Nunes. Modelo de otimização multiobjetivo para roteamento em redes sem fio. 2017. 104 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2017.