Advertisement

A Polynomial-Time Branching Procedure for the Multiprocessor Scheduling Problem

  • Ricardo C. Corrêa
  • Afonso Ferreira
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1685)

Abstract

We present and analyze a branching procedure suitable for best-first branch-and-bound algorithms for solving multiprocessor scheduling problems. The originality of this branching procedure resides mainly in its ability to enumerate all feasible solutions without generating duplicated subproblems. This procedure is shown to be polynomial in time and space complexities.

Keywords

Direct Acyclic Graph Search Tree Precedence Constraint Precedence Relation Multiprocessor System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. [1]
    T. Casavant and J. Kuhl. A taxonomy of scheduling in general-purpose distributed computing systems. IEEE Trans. on Software Engineering, 14(2), 1988.Google Scholar
  2. [2]
    P.C. Chang and Y.S. Jiang. A State-Space Search Approach for Parallel Processor Scheduling Problems with Arbitrary Precedence Relations. European Journal of Operational Research, 77:208–223, 1994.Google Scholar
  3. [3]
    M. Cosnard and D. Trystram. Parallel Algorithms and Architectures. International Thomson Computer Press, 1995.Google Scholar
  4. [4]
    M. Garey and D. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. W. F. Freeman, 1979.Google Scholar
  5. [5]
    H. Kasahara and S. Narita. Practical multiprocessor scheduling algorithms for efficient parallel processing. IEEE Trans. on Computers, C-33(11):1023–1029, 1984.Google Scholar
  6. [6]
    Y.-K. Kwok and I. Ahmad. Otimal and near-optimal allocation of precedenceconstrained tasks to parallel processors: defying the high complexity using effective search techniques. In Proceedings Int. Conf. Parallel Processing, 1998.Google Scholar
  7. [7]
    L. Mitten. Branch-and-bound methods: General formulation and properties. Operations Research, 18:24–34, 1970. Errata in Operations Research, 19:550, 1971.Google Scholar
  8. [8]
    M. Norman and P. Thanisch. Models of machines and computations for mapping in multicomputers. ACM Computer Surveys, 25(9):263–302, Sep 1993.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Ricardo C. Corrêa
    • 1
  • Afonso Ferreira
    • 2
  1. 1.Departamento de ComputaçãoUniversidade Fedeal do CearáFortalezaBrazil
  2. 2.CNRS. Projet SLOOP, INRIA Sophia AntipolisSophia Antipolis CedexFrance

Personalised recommendations