Minimal communication in a distributed discrete-event system

Abstract

Abstract-This paper deals with distributed discrete-event systems, in which agents (or local sites) are required to communicate in order to perform some specified tasks. Associated with each agent is a finite-state automaton that captures the required tasks to be performed at that site. The problem considered is that each agent must be able to distinguish between the states of its automaton. To help it disambiguate states, an agent uses a combination of direct observation (obtained from sensor readings available to that agent) and communicated information (obtained from sensor readings available to another agent). Since communication may be costly, a strategy to minimize communication between sites is developed. The complexity of the solution reflects the interdependence of the agents' communication protocols. That is, the decision to communicate the occurrence of an event relies on which event sequences are indistinguishable to an agent, which, in turn, is a result of what has already been communicated to that agent.

Application of supervisory control theory to theme park vehicles

“…The local control commands issued by S 1 and S 2 will be put together according to a certain fusion rule, e.g., the conjunctive rule which defines the global control command as the intersection of all local commands (Rudie and Wonham 1992), or the disjunctive rule which defines the global control command as the union of local commands (Yoo and Lafortune 2002), or the combination of both conjunctive and disjunctive rules (Yoo and Lafortune 2002). To make control more effective, communication may be allowed among local supervisors (see e.g., Rudie et al 2003), and to reduce potential costs of maintaining sensor readings in a partially observed system sensors may be activated only when necessary (see e.g., Wang et al 2010). …”

Supervisor Localization: A Top-Down Approach to Distributed Control of Discrete-Event Systems

“…This assumption was later dropped in [12,48,58,66], where a decentralized solution was sought to a possibly indecomposable specification. More recently, this architecture was extended by permitting communications among decentralized supervisors, which thus may cooperatively resolve ambiguity due to 'myopic' local observation [5,46,47,55,59]. …”

Failure Diagnosis for Distributed Stochastic Discrete Event Systems

“…DESs with decentralized information can be classified into distributed DESs [3,7,8] and decentralized DESs [4,9]. Meanwhile, the methods of diagnosis are classified into distributed diagnosis and decentralized diagnosis.…”