Mobile edge computing and machine learning in the internet of unmanned aerial vehicles: a survey
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 …
the paradigm of the Internet of UAVs, due to their characteristics of flexibility, mobility, and …
Energy-efficient UAV-assisted mobile edge computing: Resource allocation and trajectory optimization
In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing
(MEC) with the objective to optimize computation offloading with minimum UAV energy …
(MEC) with the objective to optimize computation offloading with minimum UAV energy …
A survey on computation offloading modeling for edge computing
H Lin, S Zeadally, Z Chen, H Labiod, L Wang - Journal of Network and …, 2020 - Elsevier
As a promising technology, edge computing extends computation, communication, and
storage facilities toward the edge of a network. This new computing paradigm opens up new …
storage facilities toward the edge of a network. This new computing paradigm opens up new …
Computation offloading in LEO satellite networks with hybrid cloud and edge computing
Low earth orbit (LEO) satellite networks can break through geographical restrictions and
achieve global wireless coverage, which is an indispensable choice for future mobile …
achieve global wireless coverage, which is an indispensable choice for future mobile …
Deep reinforcement learning for delay-oriented IoT task scheduling in SAGIN
In this article, we investigate a computing task scheduling problem in space-air-ground
integrated network (SAGIN) for delay-oriented Internet of Things (IoT) services. In the …
integrated network (SAGIN) for delay-oriented Internet of Things (IoT) services. In the …
3D UAV trajectory design and frequency band allocation for energy-efficient and fair communication: A deep reinforcement learning approach
Unmanned Aerial Vehicle (UAV)-assisted communication has drawn increasing attention
recently. In this paper, we investigate 3D UAV trajectory design and band allocation problem …
recently. In this paper, we investigate 3D UAV trajectory design and band allocation problem …
Joint multi-task offloading and resource allocation for mobile edge computing systems in satellite iot
For multi-task mobile edge computing (MEC) systems in satellite Internet of Things (IoT),
there are dependencies between different tasks, which need to be collected and jointly …
there are dependencies between different tasks, which need to be collected and jointly …
Completion time and energy optimization in the UAV-enabled mobile-edge computing system
C Zhan, H Hu, X Sui, Z Liu… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Completion time and energy consumption of the unmanned aerial vehicle (UAV) are two
important design aspects in UAV-enabled applications. In this article, we consider a UAV …
important design aspects in UAV-enabled applications. In this article, we consider a UAV …
Flight delay prediction based on aviation big data and machine learning
Accurate flight delay prediction is fundamental to establish the more efficient airline
business. Recent studies have been focused on applying machine learning methods to …
business. Recent studies have been focused on applying machine learning methods to …
AI-assisted network-slicing based next-generation wireless networks
The integration of communications with different scales, diverse radio access technologies,
and various network resources renders next-generation wireless networks (NGWNs) highly …
and various network resources renders next-generation wireless networks (NGWNs) highly …