A BDD-Based Approach for Designing Maximally Permissive Deadlock Avoidance Policies for Complex Resource Allocation Systems
Journal article, 2015

In order to develop a computationally efficient implementation of the maximally permissive deadlock avoidance policy (DAP) for complex resource allocation systems (RAS), a recent approach focuses on the identification of a set of critical states of the underlying RAS state-space, referred to as minimal boundary unsafe states. The availability of this information enables an expedient one-step-lookahead scheme that prevents the RAS from reaching outside its safe region. The work presented in this paper seeks to develop a symbolic approach, based on binary decision diagrams (BDDs), for efficiently retrieving the (minimal) boundary unsafe states from the underlying RAS state-space. The presented results clearly demonstrate that symbolic computation enables the deployment of the maximally permissive DAP for complex RAS with very large structure and state-spaces with limited time and memory requirements. Furthermore, the involved computational costs are substantially reduced through the pertinent exploitation of the special structure that exists in the considered problem.

supervisory control theory

discrete event systems

Binary decision diagrams

resource allocation systems

deadlock avoidance

maximal permissiveness

Author

Zhennan Fei

Chalmers, Signals and Systems, Systems and control, Automation

Spyros Reveliotis

Knut Åkesson

Chalmers, Signals and Systems, Systems and control, Automation

IEEE Transactions on Automation Science and Engineering

1545-5955 (ISSN)

Vol. 12 3 990-1006

Areas of Advance

Production

Subject Categories

Robotics

Control Engineering

DOI

10.1109/TASE.2014.2369858

More information

Created

10/7/2017