Wireless Mesh Networks have long been hailed as one of the most promising technologies for future high-bandwidth, high-coverage wireless networks. Consumer demand for such networks, on the other hand, has just recently caught up, making it more critical than ever to optimise WMNs to accommodate massive capacity and provide excellent QoS while being secure and fault-tolerant. Machine learning (ML) has lately gained popularity for addressing several design and administrative difficulties related to WMNs for this purpose. Key machine learning techniques are presented in this study, as well as prior attempts to apply them to WMNs, along with some known obstacles and prospective solutions. There are ideas on how machine learning could aid future research. There's also a discussion of the most current developments in the discipline.

Wireless Mesh Networks, Quality of Services, Machine Learning, Computational Intelligence