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 …

Cloud-edge orchestration for the Internet of Things: Architecture and AI-powered data processing

Y Wu - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) has been deeply penetrated into a wide range of important and
critical sectors, including smart city, water, transportation, manufacturing, and smart factory …

Deep reinforcement learning-based energy-efficient edge computing for internet of vehicles

X Kong, G Duan, M Hou, G Shen… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Mobile network operators (MNOs) allocate computing and caching resources for mobile
users by deploying a central control system. Existing studies mainly use programming and …

Mobility-aware computational offloading in mobile edge networks: a survey

SK Zaman, AI Jehangiri, T Maqsood, Z Ahmad… - Cluster …, 2021 - Springer
Technological evolution of mobile devices, such as smart phones, laptops, wearable and
other handheld devices have come up with the emergence of different user applications in …

Efficient task offloading for IoT-based applications in fog computing using ant colony optimization

MK Hussein, MH Mousa - IEEE Access, 2020 - ieeexplore.ieee.org
The current thinking concerning computations required by Internet of Things (IoT)
applications is shifting toward fog computing instead of cloud computing, thereby achieving …

Task partitioning and offloading in IoT cloud-edge collaborative computing framework: a survey

H Chen, W Qin, L Wang - Journal of Cloud Computing, 2022 - Springer
Abstract Internet of Things (IoT) is made up with growing number of facilities, which are
digitalized to have sensing, networking and computing capabilities. Traditionally, the large …

Deep Reinforcement Learning for energy-aware task offloading in join SDN-Blockchain 5G massive IoT edge network

B Sellami, A Hakiri, SB Yahia - Future Generation Computer Systems, 2022 - Elsevier
Abstract The Internet-of-Things (IoT) edge allows cloud computing services for topology and
location-sensitive distributed computing. As an immediate benefit, it improves network …

Energy-aware task scheduling and offloading using deep reinforcement learning in SDN-enabled IoT network

B Sellami, A Hakiri, SB Yahia, P Berthou - Computer Networks, 2022 - Elsevier
Abstract The fifth-generation (5G) mobile network services have made tremendous growth in
the Internet of Things (IoT) network. A counters number of battery-powered IoT devices are …

An AUV-assisted data gathering scheme based on clustering and matrix completion for smart ocean

M Huang, K Zhang, Z Zeng, T Wang… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
The oceans cover more than 71% of the Earth's surface and have a surging amount of data.
It is of great significance to seek energy-effective and ultrareliable communication and …

QoE-based task offloading with deep reinforcement learning in edge-enabled Internet of Vehicles

X He, H Lu, M Du, Y Mao… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In the transportation industry, task offloading services of edge-enabled Internet of Vehicles
(IoV) are expected to provide vehicles with the better Quality of Experience (QoE). However …