Resource scheduling in edge computing: A survey

Q Luo, S Hu, C Li, G Li, W Shi - IEEE Communications Surveys …, 2021 - ieeexplore.ieee.org
With the proliferation of the Internet of Things (IoT) and the wide penetration of wireless
networks, the surging demand for data communications and computing calls for the …

6G wireless communications networks: A comprehensive survey

M Alsabah, MA Naser, BM Mahmmod… - Ieee …, 2021 - ieeexplore.ieee.org
The commercial fifth-generation (5G) wireless communications networks have already been
deployed with the aim of providing high data rates. However, the rapid growth in the number …

6G networks: Beyond Shannon towards semantic and goal-oriented communications

EC Strinati, S Barbarossa - Computer Networks, 2021 - Elsevier
The goal of this paper is to promote the idea that including semantic and goal-oriented
aspects in future 6G networks can produce a significant leap forward in terms of system …

A survey on end-edge-cloud orchestrated network computing paradigms: Transparent computing, mobile edge computing, fog computing, and cloudlet

J Ren, D Zhang, S He, Y Zhang, T Li - ACM Computing Surveys (CSUR), 2019 - dl.acm.org
Sending data to the cloud for analysis was a prominent trend during the past decades,
driving cloud computing as a dominant computing paradigm. However, the dramatically …

Efficient offloading for minimizing task computation delay of NOMA-based multiaccess edge computing

B Zhu, K Chi, J Liu, K Yu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Multi-access edge computing (MEC) has been one promising solution to reduce the
computation delay of wireless devices. Due to the high spectrum efficiency of non …

Deep reinforcement learning for stochastic computation offloading in digital twin networks

Y Dai, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The rapid development of industrial Internet of Things (IIoT) requires industrial production
towards digitalization to improve network efficiency. Digital Twin is a promising technology to …

Mobile edge intelligence and computing for the internet of vehicles

J Zhang, KB Letaief - Proceedings of the IEEE, 2019 - ieeexplore.ieee.org
The Internet of Vehicles (IoV) is an emerging paradigm that is driven by recent
advancements in vehicular communications and networking. Meanwhile, the capability and …

Task offloading in vehicular edge computing networks: A load-balancing solution

J Zhang, H Guo, J Liu, Y Zhang - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Recently, the rapid advance of vehicular networks has led to the emergence of diverse delay-
sensitive vehicular applications such as automatic driving, auto navigation. Note that …

Deep reinforcement learning for task offloading in mobile edge computing systems

M Tang, VWS Wong - IEEE Transactions on Mobile Computing, 2020 - ieeexplore.ieee.org
In mobile edge computing systems, an edge node may have a high load when a large
number of mobile devices offload their tasks to it. Those offloaded tasks may experience …

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 …