Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions

MY Akhlaqi, ZBM Hanapi - Journal of Network and Computer Applications, 2023 - Elsevier
Many enterprise companies migrate their services and applications to the cloud to benefit
from cloud computing advantages. Meanwhile, the rapidly increasing number of connected …

Contemporary advances in multi-access edge computing: A survey of fundamentals, architecture, technologies, deployment cases, security, challenges, and directions

M Mahbub, RM Shubair - Journal of Network and Computer Applications, 2023 - Elsevier
With advancements of cloud technologies Multi-Access Edge Computing (MEC) emerged as
a remarkable edge-cloud technology to provide computing facilities to resource-restrained …

Blockchain-empowered resource allocation in Multi-UAV-enabled 5G-RAN: a multi-agent deep reinforcement learning approach

AM Seid, A Erbad, HN Abishu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In 5G and B5G networks, real-time and secure resource allocation with the common telecom
infrastructure is challenging. This problem may be more severe when mobile users are …

The 6G Ecosystem as Support for IoE and Private Networks: Vision, Requirements, and Challenges

C Serôdio, J Cunha, G Candela, S Rodriguez… - Future Internet, 2023 - mdpi.com
The emergence of the sixth generation of cellular systems (6G) signals a transformative era
and ecosystem for mobile communications, driven by demands from technologies like the …

A state-of-the-art review of task scheduling for edge computing: A delay-sensitive application perspective

A Avan, A Azim, QH Mahmoud - Electronics, 2023 - mdpi.com
The edge computing paradigm enables mobile devices with limited memory and processing
power to execute delay-sensitive, compute-intensive, and bandwidth-intensive applications …

Deep reinforcement learning-based online resource management for uav-assisted edge computing with dual connectivity

LT Hoang, CT Nguyen, AT Pham - IEEE/ACM Transactions on …, 2023 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) is a key technology towards delay-sensitive and
computation-intensive applications in future cellular networks. In this paper, we consider a …

Gasto: A fast adaptive graph learning framework for edge computing empowered task offloading

Y Li, J Li, Z Lv, H Li, Y Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Mobile edge computing (MEC) has become a research trend that solves effectively
computationally intensive and latency-sensitive tasks. MEC environments in the real world …

Optimal computation resource allocation in energy-efficient edge IoT systems with deep reinforcement learning

JA Ansere, E Gyamfi, Y Li, H Shin… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
This paper investigates a computation resource optimization problem of mobile edge
computing (MEC)-aided Internet-of-Things (IoT) devices with a reinforcement learning (RL) …

Artificial Intelligence in 6G Wireless Networks: Opportunities, Applications, and Challenges

A Alhammadi, I Shayea, AA El-Saleh… - … Journal of Intelligent …, 2024 - Wiley Online Library
Wireless technologies are growing unprecedentedly with the advent and increasing
popularity of wireless services worldwide. With the advancement in technology, profound …

Servant: a user service requirements, timeslot sacrifice, and triple benefit-aware resource and worker provisioning scheme for digital twin and MEC enhanced 6G …

M Chowdhury - International Journal of Sensor Networks, 2023 - inderscienceonline.com
To minimise the application execution latencies of 6G applications, multi-access edge
computing (MEC) technology plays an indispensable role. The digital twin (DT) is another …