Secure and latency-aware digital twin assisted resource scheduling for 5G edge computing-empowered distribution grids
Digital twin (DT) provides accurate guidance for multidimensional resource scheduling in 5G
edge computing-empowered distribution grids by establishing a digital representation of the …
edge computing-empowered distribution grids by establishing a digital representation of the …
Cloud-edge-device collaborative reliable and communication-efficient digital twin for low-carbon electrical equipment management
The real-time electrical equipment management, such as renewable energy, controllable
loads, and storage units, plays a key role in low-carbon operation of smart industrial park …
loads, and storage units, plays a key role in low-carbon operation of smart industrial park …
Federated reinforcement learning-based resource allocation for D2D-aided digital twin edge networks in 6G industrial IoT
The sixth generation (6G) is conceived to address the expected high level of requirements
(such as ultra-high-data-transmission rate, support for the highest moving speed and …
(such as ultra-high-data-transmission rate, support for the highest moving speed and …
Deep Reinforcement Learning for energy-aware task offloading in join SDN-Blockchain 5G massive IoT edge network
Abstract The Internet-of-Things (IoT) edge allows cloud computing services for topology and
location-sensitive distributed computing. As an immediate benefit, it improves network …
location-sensitive distributed computing. As an immediate benefit, it improves network …
When deep reinforcement learning meets federated learning: Intelligent multitimescale resource management for multiaccess edge computing in 5G ultradense …
Recently, smart cities, healthcare system, and smart vehicles have raised challenges on the
capability and connectivity of state-of-the-art Internet-of-Things (IoT) devices, especially for …
capability and connectivity of state-of-the-art Internet-of-Things (IoT) devices, especially for …
Firefly algorithm and learning-based geographical task scheduling for operational cost minimization in distributed green data centers
Abstract Green Data Centers (GDCs) are more and more deployed world-wide. They
integrate many renewable sources to provide clean power and decrease their operating …
integrate many renewable sources to provide clean power and decrease their operating …
Digital twin-driven collaborative scheduling for heterogeneous task and edge-end resource via multi-agent deep reinforcement learning
With the interdisciplinary advances of mobile communication and edge computing, massive
heterogeneous tasks are accessing wireless networks and competing for the edge-end …
heterogeneous tasks are accessing wireless networks and competing for the edge-end …
Deep reinforcement learning for stochastic computation offloading in digital twin networks
The rapid development of industrial Internet of Things (IIoT) requires industrial production
towards digitalization to improve network efficiency. Digital Twin is a promising technology to …
towards digitalization to improve network efficiency. Digital Twin is a promising technology to …
Dual-driven resource management for sustainable computing in the blockchain-supported digital twin IoT
Nowadays, emerging sixth-generation (6G) mobile networks, the Internet of Things (IoT),
and mobile-edge computing (MEC) technologies have played significant roles in developing …
and mobile-edge computing (MEC) technologies have played significant roles in developing …
GreenEdge: Joint green energy scheduling and dynamic task offloading in multi-tier edge computing systems
As mobile edge computing (MEC) emerges as a paradigm to meet the ever-increasing
computation demands from real-time Internet of Things (IoT) applications in 5 G era, the …
computation demands from real-time Internet of Things (IoT) applications in 5 G era, the …