Lógica Fuzzy aplicada ao gerenciamento de redes definidas por software

Abstract

This paper presents the results of a research study that utilizes Fuzzy Logic to investigate the equitable allocation of bandwidth in networks, considering various user profiles. Fuzzy Logic offers flexibility in bandwidth distribution, taking into account Fuzzy variables such as bandwidth requirements, traffic priorities, and usage patterns. The goal is to develop applications for Software-Defined Networks (SDNs) that incorporate Fuzzy Logic, thereby enhancing the efficiency of network resource allocation in complex environments. This research is motivated by the growing need for network management automation, driven by the rise of the Internet of Things (IoT) and the demand for connectivity. SDNs offer a promising approach to this automation, allowing for the separation of the logical and physical network planes and the integration of intelligent applications. Efficient bandwidth allocation is critical for optimizing network performance and user satisfaction, making this research field significant. In addition to cataloging SDN technologies, conducting a literature review on AI with an emphasis on Fuzzy Logic, and developing intelligent algorithms, this paper also presents results from a prototype implemented in Python. The analysis of these results evaluated the equity and quality of bandwidth allocations. This work contributes to the fields of SDNs and AI, highlighting how Fuzzy Logic can enhance bandwidth distribution in computer networks. Automation and efficient resource allocation are crucial to meet the demands of modern networks, and this research advances toward intelligent solutions.