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 …
[PDF][PDF] Resource allocation optimization using artificial intelligence methods in various computing paradigms: A Review
With the increasing growth of information through smart devices, increasing the quality level
of human life requires various computational paradigms presentation including the Internet …
of human life requires various computational paradigms presentation including the Internet …
DNN deployment, task offloading, and resource allocation for joint task inference in IIoT
W Fan, Z Chen, Z Hao, Y Su, F Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Joint task inference, which fully utilizes end edge cloud cooperation, can effectively enhance
the performance of deep neural network (DNN) inference services in the industrial internet of …
the performance of deep neural network (DNN) inference services in the industrial internet of …
Deep reinforcement learning based approach for online service placement and computation resource allocation in edge computing
Due to the urgent emergence of computation-intensive intelligent applications on end
devices, edge computing has been put forward as an extension of cloud computing, to …
devices, edge computing has been put forward as an extension of cloud computing, to …
Dual-driven resource management for sustainable computing in the blockchain-supported digital twin IoT
Nowadays, emerging sixth-generation (6G) mobile networks, the Internet of Things (IoT),
and mobile-edge computing (MEC) technologies have played significant roles in developing …
and mobile-edge computing (MEC) technologies have played significant roles in developing …
Cache-aided MEC for IoT: Resource allocation using deep graph reinforcement learning
With the growing demand for latency-sensitive and compute-intensive services in the
Internet of Things (IoT), multiaccess edge computing (MEC)-enabled IoT is envisioned as a …
Internet of Things (IoT), multiaccess edge computing (MEC)-enabled IoT is envisioned as a …
Joint optimization of video-based AI inference tasks in MEC-assisted augmented reality systems
The high computational complexity and energy consumption of artificial intelligence (AI)
algorithms hinder their application in augmented reality (AR) systems. However, mobile …
algorithms hinder their application in augmented reality (AR) systems. However, mobile …
Joint service caching, resource allocation and computation offloading in three-tier cooperative mobile edge computing system
L Wang, G Zhang - IEEE Transactions on Network Science and …, 2023 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) provides cloud-like computing functionalities for mobile
devices (MDs) by deploying servers at the edge of future 6G network. The cooperation …
devices (MDs) by deploying servers at the edge of future 6G network. The cooperation …
Optimal model placement and online model splitting for device-edge co-inference
Device-edge co-inference opens up new possibilities for resource-constrained wireless
devices (WDs) to execute deep neural network (DNN)-based applications with heavy …
devices (WDs) to execute deep neural network (DNN)-based applications with heavy …
Digital twin-assisted federated learning service provisioning over mobile edge networks
Federated Learning (FL) offers collaborative machine learning without data exposure, but
challenges arise in the mobile edge network (MEC) environment due to limited resources …
challenges arise in the mobile edge network (MEC) environment due to limited resources …