Deep reinforcement learning algorithm for latency-oriented IIoT resource orchestration
Due to geographical factors and resource constraints, the traditional Internet architecture
cannot meet the needs of the space–air–ground-integrated network (SAGIN) resource layout …
cannot meet the needs of the space–air–ground-integrated network (SAGIN) resource layout …
Multiagent deep-reinforcement-learning-based virtual resource allocation through network function virtualization in Internet of Things
Resource allocation is a significant task in the emerging area of Internet of Things (IoT). IoT
devices are usually low-cost devices with limited computational power and capabilities for …
devices are usually low-cost devices with limited computational power and capabilities for …
Space-air-ground integrated multi-domain network resource orchestration based on virtual network architecture: A DRL method
Traditional ground wireless communication networks cannot provide high-quality services
for artificial intelligence (AI) applications such as intelligent transportation systems (ITS) due …
for artificial intelligence (AI) applications such as intelligent transportation systems (ITS) due …
Distributed orchestration of service function chains for edge intelligence in the industrial internet of things
Network virtualization techniques are promising to overcome the obstacle of applying and
expanding costly traditional networks in the industrial Internet of things (IIoT). Artificial …
expanding costly traditional networks in the industrial Internet of things (IIoT). Artificial …
Dynamic service function chain orchestration for NFV/MEC-enabled IoT networks: A deep reinforcement learning approach
Y Liu, H Lu, X Li, Y Zhang, L Xi… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Network function virtualization (NFV) and mobile-edge computing (MEC) have been
introduced by Internet service providers (ISPs) to deal with various challenges, which hinder …
introduced by Internet service providers (ISPs) to deal with various challenges, which hinder …
Deep reinforcement learning based edge computing network aided resource allocation algorithm for smart grid
Y Chi, Y Zhang, Y Liu, H Zhu, Z Zheng, R Liu… - Ieee …, 2022 - ieeexplore.ieee.org
The dramatic increase in the volume of users and services makes scheduling network
resources for smart grids a key challenge. Network slicing is an important technology to …
resources for smart grids a key challenge. Network slicing is an important technology to …
Edge computing network resource allocation based on virtual network embedding
K Zhan, N Chen, SVN Santhosh Kumar… - International Journal …, 2022 - Wiley Online Library
It is expected that the demand for quality of service (QoS) and quality of experience (QoE) in
future 6G scenarios will continue to increase, and edge computing (EC) will continue to …
future 6G scenarios will continue to increase, and edge computing (EC) will continue to …
Multidimensional resource fragmentation-aware virtual network embedding for IoT applications in MEC networks
The proliferation of Internet of Things (IoT) applications has led to the interconnection of
multiaccess edge computing (MEC) systems through metro optical networks. To cater to …
multiaccess edge computing (MEC) systems through metro optical networks. To cater to …
Virtual Network Embedding for Task Offloading in IIoT: A DRL-Assisted Federated Learning Scheme
The Industrial Internet of Things (IIoT) promotes the deep integration of new-generation
communication technologies and industrial ecology. However, the popularity of computing …
communication technologies and industrial ecology. However, the popularity of computing …
Reinforcement learning assisted bandwidth aware virtual network resource allocation
Space-air-ground integration to support seamless coverage of ground, satellite, airborne,
and marine communications, is likely to be a key trend in the 6G era. One of several key …
and marine communications, is likely to be a key trend in the 6G era. One of several key …