Hybrid evolutionary workflow scheduling algorithm for dynamic heterogeneous distributed computational environment

The optimal workflow scheduling is one of the most important issues in heterogeneous distributed computational environments. Existing heuristic and evolutionary scheduling algorithms have their advantages and disadvantages. In this work we propose a hybrid algorithm based on heuristic methods and ge...

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Bibliographic Details
Published in:Journal of applied logic Vol. 24; pp. 50 - 61
Main Authors: Nasonov, D., Visheratin, A., Butakov, N., Shindyapina, N., Melnik, M., Boukhanovsky, A.
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.11.2017
Elsevier Science Ltd
Subjects:
Dynamic environment
Evolutionary algorithms
GAHEFT
Genetic algorithms
Heuristic
Heuristic methods
LEFT
Scheduling
Scheduling algorithms
Studies
Workflow
Workflow scheduling
Workflow software
GAHEFT
GA
Evolutionary algorithms
LEFT
Workflow scheduling
Dynamic environment
ISSN:1570-8683, 1570-8691
Online Access:Get full text
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Summary:The optimal workflow scheduling is one of the most important issues in heterogeneous distributed computational environments. Existing heuristic and evolutionary scheduling algorithms have their advantages and disadvantages. In this work we propose a hybrid algorithm based on heuristic methods and genetic algorithm (GA) that combines best characteristics of both approaches. We propose heuristic algorithm called Linewise Earliest Finish Time (LEFT) as an alternative for HEFT in initial population generation for GA. We also experimentally show efficiency of described hybrid schemas GAHEFT, GALEFT, GACH for traditional workflow scheduling as well as for variable workload in dynamically changing heterogeneous computational environment.
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ISSN:1570-8683
1570-8691
DOI:10.1016/j.jal.2016.11.013