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Advanced Hybrid Information Processing. Third EAI International Conference, ADHIP 2019, Nanjing, China, September 21–22, 2019, Proceedings, Part I

Research Article

Optimization of Rational Scheduling Method for Cloud Computing Resources Under Abnormal Network

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  • @INPROCEEDINGS{10.1007/978-3-030-36402-1_22,
        author={Lunqiang Ye},
        title={Optimization of Rational Scheduling Method for Cloud Computing Resources Under Abnormal Network},
        proceedings={Advanced Hybrid Information Processing. Third EAI International Conference, ADHIP 2019, Nanjing, China, September 21--22, 2019, Proceedings, Part I},
        proceedings_a={ADHIP},
        year={2019},
        month={11},
        keywords={Abnormal network Cloud computing Resource scheduling Genetic algorithm Ant colony algorithm},
        doi={10.1007/978-3-030-36402-1_22}
    }
    
  • Lunqiang Ye
    Year: 2019
    Optimization of Rational Scheduling Method for Cloud Computing Resources Under Abnormal Network
    ADHIP
    Springer
    DOI: 10.1007/978-3-030-36402-1_22
Lunqiang Ye,*
    *Contact email: feiyun001b@163.com

    Abstract

    When the traditional heuristic algorithm was used to schedule the cloud computing resources under the abnormal network, there was a problem that the scheduling speed was slow and the effect was poor. Aiming at the above problems, combined with the characteristics of cloud computing and the actual needs of cloud computing resource allocation, based on the advantages of genetic algorithm and ant colony algorithm, a hybrid optimal cloud computing resource scheduling algorithm was designed. The improved algorithm combines the advantages of genetic algorithm and ant colony algorithm, and the genetic algorithm can effectively improve the search efficiency; The ant colony algorithm was used in the later stage of the algorithm to improve the accuracy of the optimal solution and to complete the reasonable scheduling of cloud computing resources under the abnormal network. The results show that the hybrid algorithm was faster than the single genetic algorithm and ant colony algorithm. It only took 10 s, the resource load was more balanced, and the scheduling effect was better.

    Keywords
    Abnormal network Cloud computing Resource scheduling Genetic algorithm Ant colony algorithm
    Published
    2019-11-29
    Appears in
    SpringerLink
    http://dx.doi.org/10.1007/978-3-030-36402-1_22
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