McSad: A Monte Carlo-based end-to-end scheduling anomaly detection method for distributed real-time systems.
Xianchen ShiYian ZhuLian LiJiayu LiPublished in: Simul. Model. Pract. Theory (2023)
Keyphrases
- end to end
- monte carlo
- detection method
- real time systems
- distributed systems
- real time database systems
- admission control
- real time embedded
- timing constraints
- detection algorithm
- face detection
- markov chain
- monte carlo simulation
- importance sampling
- real time
- monte carlo methods
- anomaly detection
- scheduling problem
- embedded systems
- mobile agents
- monte carlo tree search
- adaptive sampling
- congestion control
- variance reduction
- markovian decision
- scheduling algorithm
- intrusion detection
- particle filter
- computer networks
- matrix inversion
- network traffic
- region detection
- peer to peer
- quasi monte carlo
- response time