The demand for machine learning (ML) has increased significantly in recent decades,
enabling several applications, such as speech recognition, computer vision, and …

When classifying network traffic, a key challenge is deciding when to perform the
classification, ie, after how many packets. Too early, and the decision basis is too thin to …

To keep pace with the explosive growth of Artificial Intelligence (AI) and Machine Learning
(ML)-dominated applications, distributed intelligence solutions are gaining momentum …

For the future cyber-physical system (CPS) society, it is necessary to construct digital twins
(DTs) of a real world in real time using a lot of cameras and sensors. Hence, the energy …

In existing mobile network systems, the data plane (DP) is mainly considered a pipeline
consisting of network elements end-to-end forwarding user data traffics. With the rapid …

Network congestion and packet loss pose an ever-increasing challenge to video streaming.
Despite the research efforts toward making video encoding schemes resilient to lossy …

Deep learning (DL) for network models have achieved excellent performance in the field
and are becoming a promising component in future intelligent network system …

While the concept of AI4Net has been widely discussed in the past decade and adopted in
5G, its counterpart, Net4AI, has not gained that much attention so far. This is mostly due to …

In this paper, the stochastic Takagi–Sugeno fuzzy recurrent neural networks (STSFRNNS)
with distributed delay is established based on the Takagi–Sugeno (TS) model and the fixed …

ChatGPT shows the enormous potential of large language models (LLMs). These models
can easily reach the size of billions of parameters and create training difficulties for the …