Graph models for scheduling systems with machine saturation property
Paolo Dell’Olmo () and
Monica Gentili ()
Mathematical Methods of Operations Research, 2006, vol. 63, issue 2, 329-340
Abstract:
Let $$T \, =\, \{T_1, T_2, \ldots, T_n\}$$ be a set of n independent tasks and $$\mathcal{P}=\{P_1, P_2,\ldots, P_m\}$$ a set of m processors. During each time instant, each processor can be used by a single task at most. A schedule is for each task an allocation of one or more time intervals to one or more processors. A schedule is said to be optimal if it minimizes the maximum completion time. We say a schedule S has the machine saturation property (MS property) if, at any time instant of task execution, all the machines are simultaneously busy. In this paper, we analyze the conditions under which a parallel scheduling system allows a schedule with the MS property. While for some simple models the analytical conditions can be easily stated, a graph model approach is required when conflicts of processor usage are present. For this reason, we define the class of saturated graphs that correspond to scheduling systems with the MS property. We present efficient graph recognition algorithms to verify the MS property directly on some classes of saturated graphs Copyright Springer-Verlag 2006
Keywords: Makespan; Multiprocessor task scheduling; Polynomial algorithms; Intersection graphs (search for similar items in EconPapers)
Date: 2006
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1007/s00186-005-0016-6 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:mathme:v:63:y:2006:i:2:p:329-340
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/00186
DOI: 10.1007/s00186-005-0016-6
Access Statistics for this article
Mathematical Methods of Operations Research is currently edited by Oliver Stein
More articles in Mathematical Methods of Operations Research from Springer, Gesellschaft für Operations Research (GOR), Nederlands Genootschap voor Besliskunde (NGB)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().