Offloading using traditional optimization and machine learning in federated cloud–edge–fog systems: A survey

B Kar, W Yahya, YD Lin, A Ali - IEEE Communications Surveys …, 2023 - ieeexplore.ieee.org
The huge amount of data generated by the Internet of Things (IoT) devices needs the
computational power and storage capacity provided by cloud, edge, and fog computing …

Edge computing on IoT for machine signal processing and fault diagnosis: A review

S Lu, J Lu, K An, X Wang, Q He - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Edge computing is an emerging paradigm that offloads the computations and analytics
workloads onto the Internet of Things (IoT) edge devices to accelerate the computation …

Deep reinforcement learning for energy-efficient computation offloading in mobile-edge computing

H Zhou, K Jiang, X Liu, X Li… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Mobile-edge computing (MEC) has emerged as a promising computing paradigm in the 5G
architecture, which can empower user equipments (UEs) with computation and energy …

Energy-optimized partial computation offloading in mobile-edge computing with genetic simulated-annealing-based particle swarm optimization

J Bi, H Yuan, S Duanmu, MC Zhou… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Smart mobile devices (SMDs) can meet users' high expectations by executing computational
intensive applications but they only have limited resources, including CPU, memory, battery …

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 …

A cooperative partial computation offloading scheme for mobile edge computing enabled Internet of Things

Z Ning, P Dong, X Kong, F **a - IEEE Internet of Things Journal, 2018 - ieeexplore.ieee.org
With the evolutionary development of latency sensitive applications, delay restriction is
becoming an obstacle to run sophisticated applications on mobile devices. Partial …

Delay-aware and energy-efficient computation offloading in mobile-edge computing using deep reinforcement learning

L Ale, N Zhang, X Fang, X Chen… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) is considered as the enabling platform for a variety of promising
applications, such as smart transportation and smart city, where massive devices are …

Multi-access edge computing: A survey

A Filali, A Abouaomar, S Cherkaoui, A Kobbane… - IEEE …, 2020 - ieeexplore.ieee.org
Multi-access Edge Computing (MEC) is a key solution that enables operators to open their
networks to new services and IT ecosystems to leverage edge-cloud benefits in their …

Com-DDPG: Task offloading based on multiagent reinforcement learning for information-communication-enhanced mobile edge computing in the internet of vehicles

H Gao, X Wang, W Wei, A Al-Dulaimi… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The emergence of the Internet of Vehicles (IoV) introduces challenges regarding
computation-intensive and time-sensitive related services for data processing and …

Imitation learning enabled task scheduling for online vehicular edge computing

X Wang, Z Ning, S Guo, L Wang - IEEE Transactions on Mobile …, 2020 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is a promising paradigm based on the Internet of vehicles
to provide computing resources for end users and relieve heavy traffic burden for cellular …