Automatic failure detection with Conditional-Belief supervisors

Abstract

Failures of a software system are detected by a supervisor, a separate unit which observes the inputs and outputs of the system and reports its failures in real-time. The supervisor determines whether a failure has occurred by comparing the observed and the specified behavior. The specification of behavior is assumed to be expressed in a formalism based on communicating extended finite state machines (specifically, ITU-T SDL). The supervisor must tolerate legal behavioral alternatives resulting from nondeterminisms in the specification. The computational costs of considering such alternatives can be fairly high. The paper presents the Conditional-Belief (CB) theory that reduces the cost of consideration of alternatives by using conditional-beliefs to represent sets of legal behavioral alternatives. The paper reviews belief-based supervision, introduces the CB theory, and outlines an algorithm for conversion of a class of SDL specification to a CB supervisor model. It describes a demonstration system developed to evaluate CB supervision, and summarizes failure detection and computational cost results for the supervisor of the control program of a small telephone exchange.