Abstract Machine Learning (ML) has been enjoying an unprecedented surge in applications
that solve problems and enable automation in diverse domains. Primarily, this is due to the …

Currently, the network traffic control systems are mainly composed of the Internet core and
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …

Today's advancements in wireless communication technologies have resulted in a
tremendous volume of data being generated. Most of our information is part of a widespread …

Machine learning is widely used to solve networking challenges, ranging from traffic
classification and anomaly detection to network configuration. However, machine learning …

Huge amounts of data are circulating in the digital world in the era of the Industry 5.0
revolution. Machine learning is experiencing success in several sectors such as intelligent …

The network traffic prediction problem involves predicting characteristics of future network
traffic from observations of past traffic. Network traffic prediction has a variety of applications …

Wireless mesh network is prevalent for providing a decentralized access for users. For a
wireless mesh backbone network, it has obtained extensive attention because of its large …

Emerging applications---cloud computing, the internet of things, and augmented/virtual
reality---demand responsive, secure, and scalable datacenter networks. These networks …

Road transportation is the largest and complex nonlinear entity of the traffic management
system. Accurate prediction of traffic-related information is necessary for an effective …

Optimization approaches in machine learning (ML) are essential for training models to
obtain high performance across numerous domains. The article provides a comprehensive …