Wireless powered mobile edge computing networks: A survey

X Wang, J Li, Z Ning, Q Song, L Guo, S Guo… - ACM Computing …, 2023 - dl.acm.org
Wireless Powered Mobile Edge Computing (WPMEC) is an integration of Mobile Edge
Computing (MEC) and Wireless Power Transfer (WPT) technologies, to both improve …

[HTML][HTML] Impacts of intelligent transportation systems on energy conservation and emission reduction of transport systems: A comprehensive review

Z Lv, W Shang - Green Technologies and Sustainability, 2023 - Elsevier
With the development of smart cities, new requirements have been put forward for the
control of carbon emissions (CEs) in the transportation system. Intelligent transportation …

Mobile edge computing and machine learning in the internet of unmanned aerial vehicles: a survey

Z Ning, H Hu, X Wang, L Guo, S Guo, G Wang… - ACM Computing …, 2023 - dl.acm.org
Unmanned Aerial Vehicles (UAVs) play an important role in the Internet of Things and form
the paradigm of the Internet of UAVs, due to their characteristics of flexibility, mobility, and …

Mobility-aware proactive edge caching for connected vehicles using federated learning

Z Yu, J Hu, G Min, Z Zhao, W Miao… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Content Caching at the edge of vehicular networks has been considered as a promising
technology to satisfy the increasing demands of computation-intensive and latency-sensitive …

Intelligent edge computing in internet of vehicles: A joint computation offloading and caching solution

Z Ning, K Zhang, X Wang, L Guo, X Hu… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Recently, Internet of Vehicles (IoV) has become one of the most active research fields in
both academic and industry, which exploits resources of vehicles and Road Side Units …

Mobility-aware cooperative caching in vehicular edge computing based on asynchronous federated and deep reinforcement learning

Q Wu, Y Zhao, Q Fan, P Fan, J Wang… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Vehicular edge computing (VEC) can learn and cache most popular contents for vehicular
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …

RL/DRL meets vehicular task offloading using edge and vehicular cloudlet: A survey

J Liu, M Ahmed, MA Mirza, WU Khan… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
The last two decades have seen a clear trend toward crafting intelligent vehicles based on
the significant advances in communication and computing paradigms, which provide a safer …

Deep reinforcement learning for collaborative edge computing in vehicular networks

M Li, J Gao, L Zhao, X Shen - IEEE Transactions on Cognitive …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a promising technology to support mission-critical
vehicular applications, such as intelligent path planning and safety applications. In this …

Solving dynamic traveling salesman problems with deep reinforcement learning

Z Zhang, H Liu, MC Zhou… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A traveling salesman problem (TSP) is a well-known NP-complete problem. Traditional TSP
presumes that the locations of customers and the traveling time among customers are fixed …

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 …