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 …

Energy-efficient UAV scheduling and probabilistic task offloading for digital twin-empowered consumer electronics industry

X Huang, Y Zhang, Y Qi, C Huang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The digital twin (DT)–powered consumer electronics industry has been proposed to create
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 …

Hybrid machine learning approach for resource allocation of digital twin in UAV-aided Internet-of-Vehicles networks

B Hazarika, K Singh, A Paul… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …

Dense multi-agent reinforcement learning aided multi-UAV information coverage for vehicular networks

H Fu, J Wang, J Chen, P Ren, Z Zhang… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
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 …

DRL-based federated learning for efficient vehicular caching management

P Singh, B Hazarika, K Singh, C Pan… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
In this study, we present a hybrid deep reinforcement learning (DRL) algorithm, trained
using vehicular federated learning (VFL), specifically tailored for dynamic vehicular networks …

Enhancing vehicular networks with hierarchical O-RAN slicing and federated DRL

B Hazarika, P Saikia, K Singh… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
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 …

On the interplay of artificial intelligence and space-air-ground integrated networks: A survey

A Bakambekova, N Kouzayha… - IEEE Open Journal of …, 2024 - ieeexplore.ieee.org
Space-Air-Ground Integrated Networks (SAGINs), which incorporate space and aerial
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 …

Augmented multi-agent DRL for multi-incentive task prioritization in vehicular crowdsensing

P Singh, B Hazarika, K Singh… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Vehicular crowdsensing (VCS) within the social Internet of Vehicles (IoV) significantly
advances urban transportation management by enhancing road safety, traffic efficiency, and …