An incremental reinforcement learning scheduling strategy for data-intensive scientific workflows in the cloud.
André NascimentoVítor SilvaAline PaesDaniel de OliveiraPublished in: Concurr. Comput. Pract. Exp. (2021)
Keyphrases
- data intensive
- scheduling strategy
- scientific workflows
- grid computing
- reinforcement learning
- web services
- distributed computing
- cloud computing
- scientific data
- data management
- scheduling algorithm
- load balancing
- service oriented
- semantic annotation
- peer to peer
- resource management
- quality of service
- data access
- computing environments
- virtual machine
- machine learning
- big data
- multi agent
- round robin
- file system
- fault tolerance
- data center
- semi automatic
- workflow systems
- distributed databases
- distributed environment
- social media
- case study
- data collection