Abstract
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.
Keywords
- 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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Nasonov, D., Butakov, N., Balakhontseva, M., Knyazkov, K., Boukhanovsky, A.V. (2014). Hybrid Evolutionary Workflow Scheduling Algorithm for Dynamic Heterogeneous Distributed Computational Environment. In: de la Puerta, J., et al. International Joint Conference SOCO’14-CISIS’14-ICEUTE’14. Advances in Intelligent Systems and Computing, vol 299. Springer, Cham. https://doi.org/10.1007/978-3-319-07995-0_9
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DOI: https://doi.org/10.1007/978-3-319-07995-0_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07994-3
Online ISBN: 978-3-319-07995-0
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