Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …
Machine learning for large-scale optimization in 6g wireless networks
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
PPSF: A privacy-preserving and secure framework using blockchain-based machine-learning for IoT-driven smart cities
With the evolution of the Internet of Things (IoT), smart cities have become the mainstream of
urbanization. IoT networks allow distributed smart devices to collect and process data within …
urbanization. IoT networks allow distributed smart devices to collect and process data within …
Cost minimization-oriented computation offloading and service caching in mobile cloud-edge computing: An A3C-based approach
This paper considers computation offloading and service caching in a three-tier mobile
cloud-edge computing structure, in which Mobile Users (MUs) have subscribed to the Cloud …
cloud-edge computing structure, in which Mobile Users (MUs) have subscribed to the Cloud …
MADDPG-based joint service placement and task offloading in MEC empowered air-ground integrated networks
Multiaccess edge computing (MEC) empowered air–ground integrated networks (AGINs)
hold great promise in delivering accessible computing services for users and Internet of …
hold great promise in delivering accessible computing services for users and Internet of …
Distributed task offloading and resource purchasing in noma-enabled mobile edge computing: Hierarchical game theoretical approaches
As the computing resources and the battery capacity of mobile devices are usually limited, it
is a feasible solution to offload the computation-intensive tasks generated by mobile devices …
is a feasible solution to offload the computation-intensive tasks generated by mobile devices …
A unified blockchain-semantic framework for wireless edge intelligence enabled web 3.0
Web 3.0 enables user-generated contents and user-selected authorities. With the help of
decentralized wireless edge computing architectures, Web 3.0 allows users to read, write …
decentralized wireless edge computing architectures, Web 3.0 allows users to read, write …
Mean-field learning for edge computing in mobile blockchain networks
Blockchain has been leveraged to secure transactions for the m-commerce. However, the
intensive computation in the mining process restricts the participation of mobile devices …
intensive computation in the mining process restricts the participation of mobile devices …
Reinforcement learning-empowered mobile edge computing for 6G edge intelligence
Mobile edge computing (MEC) is considered a novel paradigm for computation-intensive
and delay-sensitive tasks in fifth generation (5G) networks and beyond. However, its …
and delay-sensitive tasks in fifth generation (5G) networks and beyond. However, its …
Environment-aware AUV trajectory design and resource management for multi-tier underwater computing
The Internet of underwater things (IoUT) is envisioned to be an essential part of maritime
activities. Given the IoUT devices' wide-area distribution and constrained transmit power …
activities. Given the IoUT devices' wide-area distribution and constrained transmit power …