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Author ORCID Identifier
Open Access Dissertation
Doctor of Philosophy (PhD)
Electrical and Computer Engineering
Year Degree Awarded
Month Degree Awarded
C Mani Krishna
Artificial Intelligence and Robotics | Computer and Systems Architecture | Computer Engineering | Controls and Control Theory | Robotics | Systems Architecture | Theory and Algorithms
Cyber-physical systems frequently have to use massive redundancy to meet application requirements for high reliability. While such redundancy is required, it can be activated adaptively, based on the current state of the controlled plant. Most of the time the physical plant is in a state that allows for a lower level of fault-tolerance. Avoiding the continuous deployment of massive fault-tolerance will greatly reduce the workload of CPSs. In this dissertation, we demonstrate a software simulation framework (AdaFT) that can automatically generate the sub-spaces within which our adaptive fault-tolerance can be applied. We also show the theoretical benefits of AdaFT, and its actual implementation in several real-world CPSs.
Xu, Ye, "ADAFT: A RESOURCE-EFFICIENT FRAMEWORK FOR ADAPTIVE FAULT-TOLERANCE IN CYBER-PHYSICAL SYSTEMS" (2017). Doctoral Dissertations. 1087.
Artificial Intelligence and Robotics Commons, Computer and Systems Architecture Commons, Controls and Control Theory Commons, Robotics Commons, Systems Architecture Commons, Theory and Algorithms Commons