An intelligent Hybrid-Q Learning clustering approach and resource management within heterogeneous cluster networks based on reinforcement learning.
Fahad Razaque MughalJingsha HeNafei ZhuMutiq AlmutiqFayaz Ali DharejoDeepak Kumar JainSaqib HussainZulfiqar Ali ZardariPublished in: Trans. Emerg. Telecommun. Technol. (2024)
Keyphrases
- resource management
- reinforcement learning
- clustering algorithm
- data clustering
- function approximation
- hierarchical clustering
- management system
- cluster analysis
- network resources
- reinforcement learning algorithms
- resource allocation
- call admission control
- heterogeneous networks
- optimal policy
- state space
- end to end qos
- k means
- model free
- resource utilization
- resource usage
- learning algorithm
- data points
- grid computing
- intelligent agents
- computing resources
- quality of service
- cooperative
- cluster centers
- action selection
- stochastic approximation
- multi agent reinforcement learning
- temporal difference
- intra cluster
- clustering method
- heterogeneous wireless networks
- temporal difference learning
- blocking probability
- multi agent
- machine learning
- policy iteration
- admission control
- data objects
- markov decision processes
- grid environment
- cellular networks
- grid systems
- reward function
- real time