Analysis of Multi-Organization Scheduling Algorithms

  • Johanne Cohen
  • Daniel Cordeiro
  • Denis Trystram
  • Frédéric Wagner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6272)


In this paper we consider the problem of scheduling on computing platforms composed of several independent organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization provides both resources and tasks and follows its own objectives. We are interested in the best way to minimize the makespan on the entire platform when the organizations behave in a selfish way.

We study the complexity of the MOSP problem with two different local objectives – makespan and average completion time – and show that MOSP is NP-Hard in both cases. We formally define a selfishness notion, by means of restrictions on the schedules. We prove that selfish behavior imposes a lower bound of 2 on the approximation ratio for the global makespan.

We present various approximation algorithms of ratio 2 which validate selfishness restrictions. These algorithms are experimentally evaluated through simulation, exhibiting good average performances.


Approximation Ratio Local Objective Local Constraint Short Processing Time Unrelated Parallel Machine 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Johanne Cohen
    • 1
  • Daniel Cordeiro
    • 2
  • Denis Trystram
    • 2
  • Frédéric Wagner
    • 2
  1. 1.Laboratoire d’Informatique PRiSMUniversité de Versailles St-Quentin-en-YvelinesVersailles CedexFrance
  2. 2.LIGGrenoble UniversityMontbonnot Saint-MartinFrance

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