Double deep Q-network based dynamic framing offloading in vehicular edge computing
With the rapid development of Artificial Intelligence (AI) and the Internet of Vehicles (IoV),
there is an increasing demand for deploying various intelligent applications on vehicles …
there is an increasing demand for deploying various intelligent applications on vehicles …
Deep reinforcement learning‐based resource allocation in multi‐access edge computing
Network architects and engineers face challenges in meeting the increasing complexity and
low‐latency requirements of various services. To tackle these challenges, multi‐access …
low‐latency requirements of various services. To tackle these challenges, multi‐access …
Cache-assisted collaborative task offloading and resource allocation strategy: A metareinforcement learning approach
S Chen, L Rui, Z Gao, W Li, X Qiu - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Multiaccess edge computing (MEC) provides users with better Quality of Experience (QoE)
via offloading tasks to the nearby edge. However, the emergence of new Internet of Things …
via offloading tasks to the nearby edge. However, the emergence of new Internet of Things …
Machine learning methods for service placement: a systematic review
P Keshavarz Haddadha, MH Rezvani… - Artificial Intelligence …, 2024 - Springer
With the growth of real-time and latency-sensitive applications in the Internet of Everything
(IoE), service placement cannot rely on cloud computing alone. In response to this need …
(IoE), service placement cannot rely on cloud computing alone. In response to this need …
Multiagent reinforcement learning-based orbital edge offloading in SAGIN supporting Internet of Remote Things
S Zhang, A Liu, C Han, X Liang, X Xu… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
We investigate a computing task scheduling problem in space–air–ground integrated
network (SAGIN) for Internet of Remote Things (IoRT). In the considered scenario, the …
network (SAGIN) for Internet of Remote Things (IoRT). In the considered scenario, the …
Fast adaptive task offloading and resource allocation via multiagent reinforcement learning in heterogeneous vehicular fog computing
Z Gao, L Yang, Y Dai - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
In vehicular fog computing, task offloading enables mobile vehicles (MVs) to offer ultralow
latency services for computation-intensive tasks. Nevertheless, the edge server (ES) may …
latency services for computation-intensive tasks. Nevertheless, the edge server (ES) may …
In-network placement of delay-constrained computing tasks in a softwarized intelligent edge
Abstract Future sixth-generation (6G) networks will rely on the synergies of edge computing
and machine learning (ML) to build an intelligent edge, where communication and …
and machine learning (ML) to build an intelligent edge, where communication and …
GASTO: A fast adaptive graph learning framework for edge computing empowered task offloading
Mobile edge computing (MEC) has become a research trend that solves effectively
computationally intensive and latency-sensitive tasks. MEC environments in the real world …
computationally intensive and latency-sensitive tasks. MEC environments in the real world …
Task offloading and resource allocation for industrial Internet of Things: A double-dueling deep Q-network approach
W Cheng, X Liu, X Wang, G Nie - IEEE Access, 2022 - ieeexplore.ieee.org
With the development of 5G technology, Mobile Edge Computing (MEC) has become a
promising technology that is widely used in the Industrial Internet of Things (IIoT) and other …
promising technology that is widely used in the Industrial Internet of Things (IIoT) and other …
Computation offloading and resource allocation in failure-aware vehicular edge computing
The advent of Intelligent Cyber-Physical Transportation Systems (ICTS) has not only
accelerated the reformation and evolvement of smart transportation, but also ushered in a …
accelerated the reformation and evolvement of smart transportation, but also ushered in a …