URLLC resource slicing and scheduling for trustworthy 6G vehicular services: A federated reinforcement learning approach.
Min HaoDongdong YeSiming WangBeihai TanRong YuPublished in: Phys. Commun. (2021)
Keyphrases
- reinforcement learning
- grid environment
- resource allocation
- utility computing
- resource constraints
- service oriented
- web services
- resource consumption
- scheduling algorithm
- information resources
- resource sharing
- service providers
- resource requirements
- scarce resources
- digital libraries
- function approximation
- grid computing
- heterogeneous networks
- information services
- end users
- service composition
- multi agent
- service discovery
- urban areas
- resource discovery
- context aware
- reinforcement learning algorithms
- ubiquitous computing
- scheduling problem
- model free
- service oriented architecture
- resource management
- resource utilization
- markov decision processes
- data dissemination
- state space
- agent receives
- machine learning