Hybrid Evolutionary Workflow Scheduling Algorithm for Dynamic Heterogeneous Distributed Computational Environment

  • Denis Nasonov
  • Nikolay Butakov
  • Marina Balakhontseva
  • Konstantin Knyazkov
  • Alexander V. Boukhanovsky
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 299)


The optimal workflow scheduling is one of the most important issues in heterogeneous distributed computational environment. Existing heuristic and evolutionary scheduling algorithms have their advantages and disadvantages. In this work we propose a hybrid algorithm based on Heterogeneous Earliest Finish Time heuristic and genetic algorithm that combines best characteristics of both approaches. We also experimentally show its efficiency for variable workload in dynamically changing heterogeneous computational environment.


Schedule Algorithm Hybrid Algorithm Traditional Genetic Algorithm Heterogeneous Earliest Finish Time Heterogeneous Computational Environment 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Denis Nasonov
    • 1
  • Nikolay Butakov
    • 1
  • Marina Balakhontseva
    • 1
  • Konstantin Knyazkov
    • 1
  • Alexander V. Boukhanovsky
    • 2
  1. 1.ITMO UniversitySaint-Petersburg, Russian FederationRussia
  2. 2.Netherlands Institute for Advanced Study in the Humanities and Social SciencesWassenaarThe Netherlands

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