Applications of multi-agent reinforcement learning in future internet: A comprehensive survey

T Li, K Zhu, NC Luong, D Niyato, Q Wu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Future Internet involves several emerging technologies such as 5G and beyond 5G
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …

Edge intelligence—research opportunities for distributed computing continuum systems

VC Pujol, PK Donta, A Morichetta… - IEEE Internet …, 2023 - ieeexplore.ieee.org
Edge intelligence and, by extension, any distributed computing continuum system will bring
to our future society a plethora of new and useful applications, which will certainly …

A game-based deep reinforcement learning approach for energy-efficient computation in MEC systems

M Chen, W Liu, T Wang, S Zhang, A Liu - Knowledge-Based Systems, 2022 - Elsevier
Many previous energy-efficient computation optimization works for mobile edge computing
(MEC) systems have been based on the assumption of synchronous offloading, where all …

LiMPO: Lightweight mobility prediction and offloading framework using machine learning for mobile edge computing

SK Zaman, AI Jehangiri, T Maqsood, N Haq, AI Umar… - Cluster …, 2023 - Springer
Several applications have emerged with the proliferation of mobile devices to provide
communication, learning, social networking, entertainment, and community computing …

Blockchain-empowered collaborative task offloading for cloud-edge-device computing

S Yao, M Wang, Q Qu, Z Zhang… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
How to enable high-performance task offloading and preserve the trust between participants
is imperative yet nontrivial to the Cloud-Edge-Device (CED) computing, mainly because the …

Reinforcement learning-empowered mobile edge computing for 6G edge intelligence

P Wei, K Guo, Y Li, J Wang, W Feng, S Jin, N Ge… - Ieee …, 2022 - ieeexplore.ieee.org
Mobile edge computing (MEC) is considered a novel paradigm for computation-intensive
and delay-sensitive tasks in fifth generation (5G) networks and beyond. However, its …

Urban‒rural disparities in household energy and electricity consumption under the influence of electricity price reform policies

Y Nie, G Zhang, L Zhong, B Su, X Xi - Energy Policy, 2024 - Elsevier
The gap in electricity consumption between urban and rural households under the influence
of electricity price reform policies remain largely unexplored. We construct a mechanistic …

Large-scale computation offloading using a multi-agent reinforcement learning in heterogeneous multi-access edge computing

Z Gao, L Yang, Y Dai - IEEE Transactions on Mobile Computing, 2022 - ieeexplore.ieee.org
Recently, existing computation offloading methods have provided extremely low service
latency for mobile users (MUs) in multi-access edge computing (MEC). However, this …

Digital twin-assisted and mobility-aware service migration in mobile edge computing

E Bozkaya - Computer Networks, 2023 - Elsevier
Abstract Mobile Edge Computing (MEC) is emerging as one of the key technologies to
process massive amount of data at the edge of the network for upcoming 6G networks. In the …

Machine learning for service migration: a survey

N Toumi, M Bagaa, A Ksentini - IEEE Communications Surveys …, 2023 - ieeexplore.ieee.org
Future communication networks are envisioned to satisfy increasingly granular and dynamic
requirements to accommodate the application and user demands. Indeed, novel immersive …