Mushu Li

TL;DR: A network-slicing based architecture is introduced and why and where artificial intelligence (AI) should be incorporated into this architecture and the benefits and potentials of AI-based approaches in the research of NGWNs are highlighted.

TL;DR: In this paper, a UAV assisted mobile edge computing (MEC) with the objective to optimize computation offloading with minimum UAV energy consumption is studied, where the UAV plays the role of an aerial cloudlet to collect and process the computation tasks offloaded by ground users.

TL;DR: This paper studies unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) with the objective to optimize computation offloading with minimum UAV energy consumption and adopts a spatial distribution estimation technique to predict the location of ground users so that the proposed approach can still be applied.

TL;DR: Simulation results show that the proposed AI-based collaborative computing approach can adapt to a highly dynamic environment with outstanding performance and the service cost can be minimized via the optimal workload assignment and server selection in collaborative computing.

TL;DR: This tutorial paper looks into the evolution and prospect of network architecture and proposes a novel conceptual architecture for the 6th generation (6G) networks, which can facilitate three types of interplay, i.e., the interplay between digital twin and network slicing paradigms, between model-driven and data-driven methods for network management, and between virtualization and AI.