Results 21 to 30 of about 134 (87)

Digital-Twin-Enabled 6G Mobile Network Video Streaming Using Mobile Crowdsourcing [PDF]

, 2023
Digital-twin-enabled cloud-centric architecture is a promising evolution trend of sixth generation (6G) network, which brings new opportunities and challenges for mobile video streaming-related services requiring the exponentially increasing traffic ...
Qi, Lianyong, Xu, Xiaolong, Wu, Xiaotong, Yuan, Yuan, Zhang, Xuyun, Ni, Qiang   +5 more
core   +3 more sources

Knowledge-Driven Multi-Agent Reinforcement Learning for Computation Offloading in Cybertwin-Enabled Internet of Vehicles [PDF]

, 2023
By offloading computation-intensive tasks of vehicles to roadside units (RSUs), mobile edge computing (MEC) in the Internet of Vehicles (IoV) can relieve the onboard computation burden.
Sun, Ruijin, Cheng, Nan, Wang, Xiucheng, Li, Changle, Yang, Xiao   +4 more
core   +1 more source

Edge Task Migration With 6G-Enabled Network in Box for Cybertwin-Based Internet of Vehicles

, 2022
In the Internet of Vehicles (IoV), various latency-critical and data-intensive applications have recently emerged to support smart traffic solutions.
Zhu, Dawei, Xu, Xiaolong, Bilal, Muhammad   +2 more
core   +3 more sources

DEHM: An Improved Differential Evolution Algorithm using Hierarchical Multi-strategy in a Cybertwin 6G Network

, 2022
Differential evolution (DE) algorithm can be used in edge/cloud cyberspace to find an optimal solution due to its effectiveness and robustness}. With the rapid increase of the mobile traffic data and resources in a cybertwin-driven 6G network, the DE ...
Zhou, Z-H, Shojafar, Mohammad, Chowdhury, Morshed, Abawajy, Jemal   +3 more
core   +1 more source

SCADA Digital Twin and Cryptographic AMI Cyber-Twin for Smart Grid Security

Applied Sciences
Smart grids increasingly depend on tightly coupled Supervisory Control and Data Acquisition (SCADA) and Advanced Metering Infrastructure (AMI) infrastructures to enable real-time monitoring, control, and data-driven energy management.
S. Rayhan Kabir, Mohammad Kamrul Hasan, Tanja Pavleska, Salwani Abdullah   +3 more
doaj   +1 more source

Towards the neuromorphic Cyber-Twin: an architecture for cognitive defense in digital twin ecosystems

Frontiers in Big Data
IntroductionAs cyber-physical systems become increasingly virtualized, digital twins have emerged as essential components for real-time monitoring, simulation, and control.
Nida Nasir, Hussam Al Hamadi
doaj   +1 more source

Cybertwin driven resource allocation using optimized proximal policy based federated learning in 6G enabled edge environment

Digital Communications and Networks
Sixth-generation (6G) communication system promises unprecedented data density and transformative applications over different industries. However, managing heterogeneous data with different distributions in 6G-enabled multi-access edge cloud networks ...
Sowmya Madhavan, M.G. Aruna, G.P. Ramesh, Abdul Lateef Haroon Phulara Shaik, Dhulipalla Ramya Krishna   +4 more
doaj   +1 more source

Optimizing Energy and Latency in 6G Smart Cities with Edge CyberTwins

CoRR
The proliferation of IoT devices in smart cities challenges 6G networks with conflicting energy-latency requirements across heterogeneous slices. Existing approaches struggle with the energy-latency trade-off, particularly for massive scale deployments exceeding 50,000 devices km. This paper proposes an edge-aware CyberTwin framework integrating hybrid
Amine Abouaomar, Badr Ben Elallid, Nabil Benamar   +2 more
openaire   +2 more sources

Resource allocation scheduling scheme for task migration and offloading in 6G Cybertwin internet of vehicles based on DRL

IET Communications
As vehicular technology advances, intelligent vehicles generate numerous computation‐intensive tasks, challenging the computational resources of both the vehicles and the Internet of Vehicles (IoV). Traditional IoV struggles with fixed network structures
Rui Wei, Tuanfa Qin, Jinbao Huang, Ying Yang, Junyu Ren, Lei Yang   +5 more
doaj   +1 more source

Mud Ring Optimization Algorithm with Deep Learning Model for Disease Diagnosis on ECG Monitoring System. [PDF]

Sensors (Basel), 2023
Alluhaidan AS, Maashi M, Arasi MA, Salama AS, Assiri M, Alneil AA.   +5 more
europepmc   +1 more source