FS-MAC+: Troca flexível do protocolo de acesso ao meio em redes sem fio empregando aprendizado de máquina
Abstract
Wireless networks operating on open frequencies suffer from external interference and competition for the use of the spectrum, which vary in time and space. In addition, there is a great diversity of applications running on wireless networks, each with different requirements. For example, real-time voice applications require low latency and require low data throughput. On the other hand, file transfer-based applications have higher tolerance to high latency but require higher throughput. Despite this, MAC protocols do not address the dynamism of the environment and applications of today's wireless networks. To reduce this problem, we propose a platform based on machine learning for the online swap of the MAC protocol. This process adapts continuously to variations in the network. The proposal was tested and validated in real wireless environments.
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