… type of machine learning model should be generally used in the analysis of wireless networN
… Intuition suggests that rule-based models could be in principle a good match for wireless …

… a wired connection, Machine Learning (ML) related traffic will be ubiquitous in wireless
networks. Many studies have shown that traditional wireless protocols are highly inefficient or …

… The coexistence of cloud, edge, and on-device learning paradigms has led to a layered
architecture for in-network machine learning, as shown in Fig. 1. Different layers possess …

… Abstract—Wireless sensor networks (WSNs) are typically used with dynamic … , machine
learning (ML) techniques that are able to handle dynamic situations with successful learning …

… Machine learning (ML) and AI can help in uncovering the unknown properties of wireless
networks… inspection, and suggest novel ways to optimize network deployments and operations. …

… wireless network analysis is mentioned and briefly discussed in this paper. Machine learning
… , semisupervised and unsupervised based on the learning process. The availability of data …

… , bandwidth requirement, network lifetime maximization, communication protocols and state
of the art infrastructure. In this paper, the authors propose machine learning methods as an …

… First, we categorize and explain distinct aspects of AI that can address wireless network
security threats. Although wireless network security threats are well investigated in different …

… Machine learning, one of the most promising artificial intelligence (AI) tools for … and machine
learning, along with their potential applications in next-generation (NG) wireless networks. …

… existing work on machine learning for the IoT at the physical, data-link and network layer of
… of the application of machine learning in IoT beyond wireless communication. Finally, each …