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Natural Computing

A hybrid instance-intensive workflow scheduling method in private cloud environment

  • 04-01-2017
Published in:
Authors
Xin Ye
Jia Li
Sihao Liu
Jiwei Liang
Yaochu Jin
Published in
Natural Computing | Issue 4/2019

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Abstract

Aiming to solve the problem of instance-intensive workflow scheduling in private cloud environment, this paper first formulates a scheduling optimization model considering the communication time between tasks. The objective of this model is to minimize the execution time of all workflow instances. Then, a hybrid scheduling method based on the batch strategy and an improved genetic algorithm termed fragmentation based genetic algorithm is proposed according to the characters of instance-intensive cloud workflow, where task priority dispatching rules are also taken into account. Simulations are conducted to compare the proposed method with the canonical genetic algorithm and two heuristic algorithms. Our simulation results demonstrate that the proposed method can considerably enhance the search efficiency of the genetic algorithm and is able to considerably outperform the compared algorithms, in particular when the number of workflow instances is high and the computational resource available for optimization is limited.

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Title
A hybrid instance-intensive workflow scheduling method in private cloud environment
Authors
Xin Ye
Jia Li
Sihao Liu
Jiwei Liang
Yaochu Jin
Publication date
04-01-2017
Publisher
Springer Netherlands
Published in
Natural Computing / Issue 4/2019
Print ISSN: 1567-7818
Electronic ISSN: 1572-9796
DOI
https://doi.org/10.1007/s11047-016-9600-3
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