Decentralized Grid Scheduling with Evolutionary Fuzzy Systems

  • Alexander Fölling
  • Christian Grimme
  • Joachim Lepping
  • Alexander Papaspyrou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5798)


In this paper, we address the problem of finding workload exchange policies for decentralized Computational Grids using an Evolutionary Fuzzy System. To this end, we establish a non-invasive collaboration model on the Grid layer which requires minimal information about the participating High Performance and High Throughput Computing (HPC/HTC) centers and which leaves the local resource managers completely untouched. In this environment of fully autonomous sites, independent users are assumed to submit their jobs to the Grid middleware layer of their local site, which in turn decides on the delegation and execution either on the local system or on remote sites in a situation-dependent, adaptive way. We find for different scenarios that the exchange policies show good performance characteristics not only with respect to traditional metrics such as average weighted response time and utilization, but also in terms of robustness and stability in changing environments.


Fuzzy System Rule Base Transfer Policy Gaussian Membership Function Local Schedule 
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 2009

Authors and Affiliations

  • Alexander Fölling
    • 1
  • Christian Grimme
    • 1
  • Joachim Lepping
    • 1
  • Alexander Papaspyrou
    • 1
  1. 1.Robotics Research InstituteTU Dortmund UniversityDortmundGermany

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