Resilience helps real-time systems recover from faults without leaks
Resilience in labeled real-time automata
Computational Complexity
Summary
This paper looks at how certain computer systems, called labeled real-time automata, can bounce back after something goes wrong. The authors define resilience as the system's ability to return to normal after a fault without revealing that the fault happened. They also provide ways to check if a system has this resilience using special techniques called concurrent composition and observers. This work helps understand and verify intelligent systems that can recover from errors.
labeled real-time automatonresiliencefaulty eventnormalcyconcurrent compositionobserververification algorithmintelligent agent
Authors
Kuize Zhang
Abstract
In this paper, we characterize resilience for a labeled real-time automaton (LRTA). An LRTA is resilient if whenever a faulty event occurs, after sufficiently many events occur, the LRTA returns to normalcy and the occurrence of the faulty event is not leaked. The notion of resilience reflects the ability of an LRTA recovering from a faulty behavior, and hence can model an intelligent agent. We formulate one definition of resilience for an LRTA and give verification algorithms for the definition based on two basic tools --- concurrent composition and observer.