URLLC edge networks with joint optimal user association, task offloading and resource allocation: A digital twin approach
D Van Huynh, VD Nguyen… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
This paper addresses the problem of minimising latency in computation offloading with
digital twin (DT) wireless edge networks for industrial Internet-of-Things (IoT) environment …
digital twin (DT) wireless edge networks for industrial Internet-of-Things (IoT) environment …
Online learning based computation offloading in MEC systems with communication and computation dynamics
By offloading tasks from the mobile device (MD) to its nearby deployed access points (APs),
each of which is connected to one server for task processing, computation offloading can …
each of which is connected to one server for task processing, computation offloading can …
Task offloading optimization for UAV-assisted fog-enabled Internet of Things networks
X Huang, X Yang, Q Chen… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Recently, unmanned aerial vehicles (UAVs) have been considered as an efficient way to
provide enhanced coverage or relaying services to Internet of Things devices (IDs) in …
provide enhanced coverage or relaying services to Internet of Things devices (IDs) in …
On the asynchrony of computation offloading in multi-user MEC systems
Mobile edge computing (MEC) can extend the computing capability of mobile users (MUs),
by offloading computational tasks from MUs to proximal MEC servers. Specifically, offloaded …
by offloading computational tasks from MUs to proximal MEC servers. Specifically, offloaded …
Deep reinforcement learning-based joint optimization of delay and privacy in multiple-user MEC systems
Multi-access Edge Computing (MEC) enables mobile users to run various delay-sensitive
applications via offloading computation tasks to MEC servers. However, the location privacy …
applications via offloading computation tasks to MEC servers. However, the location privacy …
Intelligent service migration based on hidden state inference for mobile edge computing
X Li, S Chen, Y Zhou, J Chen… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Mobile edge computing, enabling cloud computing capabilities at edge servers, is shown to
be an effective way to enhance network performance as well as user experience. However …
be an effective way to enhance network performance as well as user experience. However …
A collaborative computational offloading strategy for latency-sensitive applications in fog networks
Network data traffic has expanded exponentially over the past decade, resulting in massive
congestion in heterogeneous networks. Nevertheless, it is nearly impossible to run latency …
congestion in heterogeneous networks. Nevertheless, it is nearly impossible to run latency …
Two-dimensional task offloading for mobile networks: An imitation learning framework
Mobile computing network is envisioned as a powerful framework to support the growing
computation-intensive applications in the era of the Internet of Things (IoT). In this paper, we …
computation-intensive applications in the era of the Internet of Things (IoT). In this paper, we …
Optimized resource allocation and time partitioning for integrated communication, sensing, and edge computing network
The diverse computational tasks generated from advanced applications are becoming more
difficult to process by mobile user equipments due to their limited computing capability and …
difficult to process by mobile user equipments due to their limited computing capability and …
Dynamic computation offloading in multi-server MEC systems: An online learning approach
As the network becomes dense, multi-server mobile edge computing (MEC) systems with
multiple candidate MEC servers, bring new opportunities to enrich user experience through …
multiple candidate MEC servers, bring new opportunities to enrich user experience through …