SEADS: Scalable and Cost-effective Dynamic Dependence Analysis of Distributed Systems via Reinforcement Learning.
Xiaoqin FuHaipeng CaiWen LiLi LiPublished in: ACM Trans. Softw. Eng. Methodol. (2021)
Keyphrases
- cost effective
- distributed systems
- reinforcement learning
- low cost
- concurrent systems
- fault tolerance
- fault tolerant
- distributed environment
- message passing
- cost effectiveness
- load balancing
- geographically distributed
- mobile agents
- power system
- multi agent
- distributed computing
- data replication
- replicated data
- case study