Saving time and cost on the scheduling of fog-based IoT applications using deep reinforcement learning approach.
Pegah GazoriDadmehr RahbariMohsen NickrayPublished in: Future Gener. Comput. Syst. (2020)
Keyphrases
- reinforcement learning
- round robin
- single image
- high cost
- scheduling problem
- machine learning
- function approximation
- resource allocation
- cloud computing
- management system
- supervised learning
- state space
- scheduling algorithm
- learning process
- total cost
- mobile computing
- model free
- database systems
- neural network
- weather conditions
- release dates