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Study on the Design of Algorithm Based on Machine Learning to Improve Cloud Computing

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  • Nawar A. Sultan

Abstract

The on-demand availability of end-user resources, in particular data storage and processing power, without a direct or customer-defined organization is referred to as "cloud computing." Distributed computing is a term widely used yet may have different meanings to different people. Customers may access both public and private data using the cloud computing model. The potential of simultaneously requesting data from several clients of the same source, which slows down the source's response time, is the most significant security risk with cloud computing. Other security concerns with cloud computing include weaknesses in the client and connection. By reducing the delay between a client's request for data and the cloud source's answer, a method was developed in our recent research to enhance the performance of cloud computing. By requesting data from several clients from the same source at once or from multiple clients from the same source or from other sources at various times in the same network, four instances were shown. By testing request and response times while protecting data from loss and noise, the findings demonstrated the system's robustness.

Suggested Citation

  • Nawar A. Sultan, 2023. "Study on the Design of Algorithm Based on Machine Learning to Improve Cloud Computing," Technium, Technium Science, vol. 10(1), pages 38-50.
  • Handle: RePEc:tec:techni:v:10:y:2023:i:1:p:38-50
    DOI: 10.47577/technium.v10i.8819
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    References listed on IDEAS

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    1. Mourad, Abood & Puchinger, Jakob & Chu, Chengbin, 2019. "A survey of models and algorithms for optimizing shared mobility," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 323-346.
    2. Paiola, Marco & Schiavone, Francesco & Grandinetti, Roberto & Chen, Junsong, 2021. "Digital servitization and sustainability through networking: Some evidences from IoT-based business models," Journal of Business Research, Elsevier, vol. 132(C), pages 507-516.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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