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Using recommender clustering to improve quality of services with sustainable virtual machines in cloud computing

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Abstract

Due to the proliferation of mobile, IoT, and Interlayer fog computing devices, the number of requests to the cloud network has increased. Today, cloud networks, new virtualization technologies, and virtual machines are essential for proper management and recommending the appropriate virtual machine to execute requests on the network. In addition, it can affect the quality of network service, and this is done by using the appropriate mapping between virtual machines to recommend web services in the cloud network better. This paper proposes an optimal method for assigning recommendation systems to the user. Finding users’ demands is essential, and the proposed method processes virtual machine input and the appropriate physical machine in cloud clusters in a parallel manner. As discussed in the results section, energy, response time, task execution in data centers, in different workflows, computational complexity, and spatial complexity are considered.

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Data availability

Data available on request from the authors. The data that support the findings of this study are available from the corresponding author, upon reasonable request.

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Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Computer Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran

    Mehran Aghaei

  2. Department of Computer Engineering, Islamic Azad University Central Tehran Branch, Tehran, Iran

    Parvaneh Asghari

  3. Department of Computer Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran

    Sepideh Adabi

  4. Department of Mathematics and Computer Science, Shahed University, Tehran, Iran

    Hamid Haj Seyyed Javadi

Authors
  1. Mehran Aghaei
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  2. Parvaneh Asghari
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  3. Sepideh Adabi
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  4. Hamid Haj Seyyed Javadi
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Contributions

MA, PA: Collected the data, contributed data or analysis tools, performed the analysis, wrote the paper, other contribution. SA, HHSJ: Conceived and designed the analysis, collected the data, contributed data or analysis tools, performed the analysis, wrote the paper.

Corresponding author

Correspondence to Parvaneh Asghari.

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Aghaei, M., Asghari, P., Adabi, S. et al. Using recommender clustering to improve quality of services with sustainable virtual machines in cloud computing. Cluster Comput 26, 1479–1493 (2023). https://doi.org/10.1007/s10586-022-03760-7

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  • DOI: https://doi.org/10.1007/s10586-022-03760-7

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