Real-time management of resource allocation systems. A discrete event systems approach.
type: Item
instance of: scholarly article
title: Real-time management of resource allocation systems. A discrete event systems approach.
zbMATH Open document ID: 1069.93002
author: Spyros Reveliotis
publication date: 2005-03-30T00:00:00Z
review text: This volume presents a methodology for resource allocation problems based on the control of discrete event systems. A resource allocation system (RAS) is defined by a set of processes which can be activated provided some resources are available. (Notice that the given definition of the size of such a system cannot be understood). The activation procedure involves a sequential logic. More specific situations, which are developed later in the chapters, are considered. The taxonomy is related to the structure of a graph representing the sequential logic (linear RAS (total order), disjunctive RAS (acyclic digraph), coordinating RAS (fork/join acyclic digraph), complex RAS (general case)), or to the resource allocation function (single-unit RAS (one unit of a unique type of resource, i.e. a binary structure), single-type RAS (several units are available), conjunctive RAS (general case)). The main danger is deadlock. To handle this, rather than imposing an order on the resource allocation function, which is too crude and sacrifices many potentially useful policies, or an ad hoc procedure specific to a detected failure, which may not be implementable in all cases, the authors propose a feedback policy based on state information utilization. This leads to nonblocking behaviour (notion of robustness). Flexibility is guaranteed then by maximal permissiveness. From the many remaining policies, an optimal one is associated to a chosen performance function (notion of optimality). Since very often the optimal solution is NP-hard, a third notion of computational realizability (scalability) is crucial in this book. Chapter two examines disjunctive-conjunctive RAS with issues related to computational complexity of optimal solutions. In chapter three, the latter issues are relaxed for single-unit RAS. Chapter four focuses on linear single-unit RAS with more specific and concrete results, which can be connected to other publications. Chapter five models RAS with Petri nets instead of …
reviewed by: A. Akutowicz
Mathematics Subject Classification ID: 93-02
Mathematics Subject Classification ID: 93C65
Mathematics Subject Classification ID: 90B80
Mathematics Subject Classification ID: 68Q17
Mathematics Subject Classification ID: 68M20
Mathematics Subject Classification ID: 93B35
zbMATH DE Number: 2150797
zbMATH Keywords: resource allocation problems
zbMATH Keywords: control of discrete event systems
zbMATH Keywords: feedback
zbMATH Keywords: nonblocking behaviour
zbMATH Keywords: robustness
zbMATH Keywords: maximal permissiveness
zbMATH Keywords: NP-hard
zbMATH Keywords: computational realizability
zbMATH Keywords: computational complexity
zbMATH Keywords: optimal solutions
zbMATH Keywords: Petri nets
zbMATH Keywords: continuous-time Markov decision processes
zbMATH Keywords: neurodynamic programming
zbMATH Keywords: optimality
MaRDI profile type: Publication
full work available at URL: b104057
OpenAlex ID: W4247253018
DOI: 10.1007/B104057
published in: International Series in Operations Research & Management Science
description: scientific article; zbMATH DE number 2150797