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Digital twins: A scientometric investigation into current progress and future directions
H Kaur, M Bhatia - Expert Systems with Applications, 2024 - Elsevier
The emergence of a modern industrial age is defined by the seamless integration of state-of-
the-art digital technologies, representing a shift that reflects the core principles of Industry …
the-art digital technologies, representing a shift that reflects the core principles of Industry …
Energy-efficient UAV scheduling and probabilistic task offloading for digital twin-empowered consumer electronics industry
The digital twin (DT)–powered consumer electronics industry has been proposed to create
virtual representations of the physical products, manufacturing processes, and …
virtual representations of the physical products, manufacturing processes, and …
Video data offloading techniques in Mobile Edge Computing: A survey
H Ma, B Ji, H Wu, L **ng - Physical Communication, 2024 - Elsevier
Driven by the Quality of Experience (QoE) demands for video analysis applications within
contexts such as smart cities, Industrial Internet of Things (IoT), and Internet of Vehicles …
contexts such as smart cities, Industrial Internet of Things (IoT), and Internet of Vehicles …
Hybrid machine learning approach for resource allocation of digital twin in UAV-aided Internet-of-Vehicles networks
In this study, we present a novel approach for efficient resource allocation in a digital twin
(DT) framework for task offloading in a UAV-aided Internet-of-Vehicles (IoV) network. Our …
(DT) framework for task offloading in a UAV-aided Internet-of-Vehicles (IoV) network. Our …
Dense multi-agent reinforcement learning aided multi-UAV information coverage for vehicular networks
With the rapid development of wireless communication networks, UAVs serving as base
stations are increasingly being applied in various scenarios which not only include edge …
stations are increasingly being applied in various scenarios which not only include edge …
DRL-based federated learning for efficient vehicular caching management
In this study, we present a hybrid deep reinforcement learning (DRL) algorithm, trained
using vehicular federated learning (VFL), specifically tailored for dynamic vehicular networks …
using vehicular federated learning (VFL), specifically tailored for dynamic vehicular networks …
Enhancing vehicular networks with hierarchical O-RAN slicing and federated DRL
With 5G technology evolving, Open Radio Access Network (O-RAN) solutions are becoming
crucial, especially for handling the diverse Quality of Service (QoS) needs in vehicular …
crucial, especially for handling the diverse Quality of Service (QoS) needs in vehicular …
On the interplay of artificial intelligence and space-air-ground integrated networks: A survey
Space-Air-Ground Integrated Networks (SAGINs), which incorporate space and aerial
networks with terrestrial wireless systems, are vital enablers of the emerging sixth …
networks with terrestrial wireless systems, are vital enablers of the emerging sixth …
Online Optimization in UAV-Enabled MEC System: Minimizing Long-Term Energy Consumption Under Adapting to Heterogeneous Demands
Y Zeng, S Chen, J Li, Y Cui, J Du - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV) can work as a flying computing platform to supply
computation services to users when the terrestrial infrastructure is insufficient or damaged …
computation services to users when the terrestrial infrastructure is insufficient or damaged …
Augmented multi-agent DRL for multi-incentive task prioritization in vehicular crowdsensing
Vehicular crowdsensing (VCS) within the social Internet of Vehicles (IoV) significantly
advances urban transportation management by enhancing road safety, traffic efficiency, and …
advances urban transportation management by enhancing road safety, traffic efficiency, and …