Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services

M Xu, H Du, D Niyato, J Kang, Z Xiong… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …

Holistic network virtualization and pervasive network intelligence for 6G

X Shen, J Gao, W Wu, M Li, C Zhou… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …

Deep reinforcement learning based resource management for DNN inference in industrial IoT

W Zhang, D Yang, H Peng, W Wu… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Performing deep neural network (DNN) inference in real time requires excessive network
resources, which poses a big challenge to the resource-limited industrial Internet of things …

Distributed task scheduling in serverless edge computing networks for the internet of things: A learning approach

Q Tang, R Xie, FR Yu, T Chen, R Zhang… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
By delegating the infrastructure management, such as provisioning or scaling to third-party
providers, serverless edge computing has recently been widely adopted in several …

Artificial intelligence implication on energy sustainability in Internet of Things: A survey

N Charef, AB Mnaouer, M Aloqaily, O Bouachir… - Information Processing …, 2023 - Elsevier
The massive number of Internet of Things (IoT) devices connected to the Internet is
continuously increasing. The operations of these devices rely on consuming huge amounts …

EdgeAdaptor: Online configuration adaption, model selection and resource provisioning for edge DNN inference serving at scale

K Zhao, Z Zhou, X Chen, R Zhou… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The accelerating convergence of artificial intelligence and edge computing has sparked a
recent wave of interest in edge intelligence. While pilot efforts focused on edge DNN …

Reliability-aware online scheduling for DNN inference tasks in mobile-edge computing

H Ma, R Li, X Zhang, Z Zhou… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Mobile-edge computing (MEC) is widely envisioned as a promising technique for
provisioning artificial intelligence (AI) capability for resource-limited Internet of Things (IoT) …

Reinforcement learning based energy-efficient collaborative inference for mobile edge computing

Y Xiao, L Xiao, K Wan, H Yang, Y Zhang… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Collaborative inference in mobile edge computing (MEC) enables mobile devices to offload
the computation tasks for the computation-intensive perception services, and the inference …

Enabling resource-efficient aiot system with cross-level optimization: A survey

S Liu, B Guo, C Fang, Z Wang, S Luo… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The emerging field of artificial intelligence of things (AIoT, AI+ IoT) is driven by the
widespread use of intelligent infrastructures and the impressive success of deep learning …

Advancements in accelerating deep neural network inference on aiot devices: A survey

L Cheng, Y Gu, Q Liu, L Yang, C Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The amalgamation of artificial intelligence with Internet of Things (AIoT) devices have seen a
rapid surge in growth, largely due to the effective implementation of deep neural network …