research-article

Cloud Computing Task Scheduling Based on Improved Differential Evolution Algorithm

Authors:

Yang SunAuthors Info & Claims

AIAM2020: Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture

Pages 118 - 124

https://doi.org/10.1145/3421766.3421785

Published: 26 October 2020 Publication History

Abstract

In recent years, the introduction of intelligent optimization algorithm into cloud computing task scheduling to deal with the problem of massive task scheduling is a research hotspot. This paper proposes three improved differential evolution cloud computing task scheduling algorithms, and the application of the improved differential evolution algorithm in cloud computing task scheduling problem is mainly studied. The maximum task completion time is optimized by improving parameters F, CR, and variation strategies. Through two sets of simulation experiments, it is proved that three improved differential evolutionary cloud task scheduling algorithms have less task completion time than the traditional differential evolution algorithm, and the bigger the number of tasks, the more obvious the performance optimization of the algorithm.

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Cited By

Sahoo HChandrasekhar Rao D(2024)Optimal Resource Allocation in Cloud Computing Using Novel ACO-DE AlgorithmArtificial Intelligence: Theory and Applications10.1007/978-981-99-8479-4_33(443-455)Online publication date: 3-Jan-2024
https://doi.org/10.1007/978-981-99-8479-4_33
Liu H(2022)Research on cloud computing adaptive task scheduling based on ant colony algorithmOptik10.1016/j.ijleo.2022.168677258(168677)Online publication date: May-2022
https://doi.org/10.1016/j.ijleo.2022.168677

Index Terms

Cloud Computing Task Scheduling Based on Improved Differential Evolution Algorithm
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
      1. Cloud computing

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AIAM2020: Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture

October 2020

566 pages

ISBN:9781450375535

DOI:10.1145/3421766

Copyright © 2020 ACM.

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Publication History

Published: 26 October 2020

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AIAM2020: 2nd International Conference on Artificial Intelligence and Advanced Manufacture

October 15 - 17, 2020

Manchester, United Kingdom

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Cited By

Sahoo HChandrasekhar Rao D(2024)Optimal Resource Allocation in Cloud Computing Using Novel ACO-DE AlgorithmArtificial Intelligence: Theory and Applications10.1007/978-981-99-8479-4_33(443-455)Online publication date: 3-Jan-2024
https://doi.org/10.1007/978-981-99-8479-4_33
Liu H(2022)Research on cloud computing adaptive task scheduling based on ant colony algorithmOptik10.1016/j.ijleo.2022.168677258(168677)Online publication date: May-2022
https://doi.org/10.1016/j.ijleo.2022.168677

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