Probability and statistics with reliability, queuing and computer science applications
Probability and statistics with reliability, queuing and computer science applications
Real-Time Systems: Design Principles for Distributed Embedded Applications
Real-Time Systems: Design Principles for Distributed Embedded Applications
Machine Learning
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Model-Based Diagnosis or Reasoning from First Principles
IEEE Intelligent Systems
Dependability Modeling and Evaluation of Phased Mission Systems: A DSPN Approach
DCCA '99 Proceedings of the conference on Dependable Computing for Critical Applications
ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
Cyber Physical Systems: Design Challenges
ISORC '08 Proceedings of the 2008 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing
Cyber-Physical Systems: A New Frontier
SUTC '08 Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008)
Discrete sensor placement problems in distribution networks
Mathematical and Computer Modelling: An International Journal
WiP Abstract: Cyber-Physical Systems for Real Time Cardiac Monitoring
ICCPS '12 Proceedings of the 2012 IEEE/ACM Third International Conference on Cyber-Physical Systems
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Cyber-physical systems (CPS) are complex net-centric hardware/software systems that can be applied to transportation, healthcare, defense, and other real-time applications. To meet the high reliability and safety requirements for these systems, proactive system health monitoring and management (HMM) techniques can be used. However, to be effective, it is necessary to ensure that the operation of the underlying HMM system does not adversely impact the normal operation of the system being monitored. In particular, it must be ensured that the operation of the HMM system will not lead to resource contentions that may prevent the system being monitored from timely completion of critical tasks. This paper presents an adaptive HMM system model that defines the fault diagnosis quality metrics and supports diagnosis requirement specifications. Based on the model, the sensor activation decision problem (SADP) is defined along with a steepest descent based heuristic algorithm to make the HMM configuration decisions that best satisfy the diagnosis quality requirements. Evaluation results show that the technique reduces the overall system resource consumption without adversely impacting the diagnosis capability of the HMM.