The existing packet forwarding technology cannot meet the increasing requirements of
Internet development due to its rigid framework. Application of artificial intelligence (AI) for …

Traffic analysis has many purposes such as evaluating the performance and security of
network operations and management. Therefore, network traffic analysis is considered vital …

A growing number of video streaming networks are incorporating machine learning (ML)
applications. The growth of video streaming services places enormous pressure on network …

The “data pipe” model used by the existing Internet protocol stack is no longer ideal for many
emerging applications, due to multimedia, multicast, mobility, machine learning, and network …

Traffic matrix (TM) prediction is essential for effective traffic engineering and network
management. Based on our analysis of real traffic traces from Wide Area Network, the traffic …

With recent achievements in deep learning over the past year, many computer and network
applications actively used deep learning architectures including convolution neural network …

Accurate traffic demand matrix (TM) prediction is essential for effective traffic engineering
and network management. Based on our analysis of real traffic traces from Wide Area …

In recent years, deep learning (DL) has prospered again due to improvements in both
computing and learning theory. Emerging studies mostly focus on the acceleration of …

Link adaptation is a promising tool of modern networks to combat the time-variant quality of
channels. Modulation and Coding Scheme (MCS) selection is essentially used for link …

Parameter Server (PS)-based architecture is widely applied in distributed machine learning
(DML), but it is still an open issue how to improve the DML performance in this frame-work …