A survey on reconfigurable intelligent surfaces assisted multi-access edge computing networks: State of the art and future challenges
This survey provides a comprehensive analysis of the integration of Reconfigurable
Intelligent Surfaces (RIS) with edge computing, underscoring RIS's critical role in advancing …
Intelligent Surfaces (RIS) with edge computing, underscoring RIS's critical role in advancing …
A survey on computation offloading in edge systems: From the perspective of deep reinforcement learning approaches
Driven by the demand of time-sensitive and data-intensive applications, edge computing
has attracted wide attention as one of the cornerstones of modern service architectures. An …
has attracted wide attention as one of the cornerstones of modern service architectures. An …
NOMA-assisted secure offloading for vehicular edge computing networks with asynchronous deep reinforcement learning
Mobile edge computing (MEC) offers promising solutions for various delay-sensitive
vehicular applications by providing high-speed computing services for a large number of …
vehicular applications by providing high-speed computing services for a large number of …
Accelerating deep learning inference via model parallelism and partial computation offloading
With the rapid development of Internet-of-Things (IoT) and the explosive advance of deep
learning, there is an urgent need to enable deep learning inference on IoT devices in Mobile …
learning, there is an urgent need to enable deep learning inference on IoT devices in Mobile …
Deep reinforcement learning-based computation offloading in uav swarm-enabled edge computing for surveillance applications
The rapid development of the Internet of Things and wireless communication has resulted in
the emergence of many latency-constrained and computation-intensive applications such as …
the emergence of many latency-constrained and computation-intensive applications such as …
Federated distributed deep reinforcement learning for recommendation-enabled edge caching
Recently, in response to the low efficiency and high transmission latency of traditional
centralized content delivery networks, especially in congested scenarios, edge caching has …
centralized content delivery networks, especially in congested scenarios, edge caching has …
Empowering non-terrestrial networks with artificial intelligence: A survey
6G networks can support global, ubiquitous and seamless connectivity through the
convergence of terrestrial and non-terrestrial networks (NTNs). Unlike terrestrial scenarios …
convergence of terrestrial and non-terrestrial networks (NTNs). Unlike terrestrial scenarios …
Stackelberg game-based dependency-aware task offloading and resource pricing in vehicular edge networks
L Zhao, S Huang, D Meng, B Liu, Q Zuo… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is an effective paradigm in Internet of Vehicles (IoV), which
allows vehicles to offload delay-sensitive tasks to nearby road side units (RSUs) for …
allows vehicles to offload delay-sensitive tasks to nearby road side units (RSUs) for …
Delay-aware optimization of fine-grained microservice deployment and routing in edge via reinforcement learning
K Peng, J He, J Guo, Y Liu, J He… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Microservices have exerted a profound impact on the development of internet applications.
Meanwhile, the growing number of mobile terminal user requests has made the …
Meanwhile, the growing number of mobile terminal user requests has made the …
Deep reinforcement learning-based task offloading and resource allocation for industrial IoT in MEC federation system
The rapid growth of the Internet of Things (IoT) has resulted in the development of intelligent
industrial systems known as Industrial IoT (IIoT). These systems integrate smart devices …
industrial systems known as Industrial IoT (IIoT). These systems integrate smart devices …