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OPTCLOUD: An Optimal Cloud Service Selection Framework Using QoS Correlation Lens.

Rakesh Ranjan Kumar1, Abhinav Tomar2, Mohammad Shameem3

  • 1Department of CSE, C V Raman Global University, Mahura, Jalna Bhubneshwar, Odisha, India.

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Selecting optimal cloud services is challenging due to complex quality of service (QoS) factors. This study introduces a new framework using Principal Component Analysis (PCA) and the Best-Worst Method (BWM) for accurate cloud service selection.

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Area of Science:

  • Computer Science
  • Information Systems

Background:

  • Cloud computing has rapidly expanded, increasing the need for effective cloud service selection.
  • Quality of Service (QoS) is a critical but complex factor in choosing cloud services, especially with diverse performance metrics.
  • Existing methods struggle with subjective user preferences and interdependencies among QoS attributes.

Purpose of the Study:

  • To propose a novel framework for optimal cloud service selection.
  • To address the challenges of subjective user preferences and correlated QoS attributes.
  • To provide users with the best cloud services meeting their specific QoS constraints.

Main Methods:

  • Development of a cloud service selection framework incorporating user preferences and QoS constraints.
  • Application of Principal Component Analysis (PCA) to handle correlations among QoS attributes.
  • Utilization of the Best-Worst Method (BWM) for preference aggregation and decision-making.

Main Results:

  • The proposed PCA-BWM algorithm effectively eliminates correlations between QoS attributes.
  • The methodology accurately identifies optimal cloud services based on user-defined QoS constraints.
  • A numerical example validates the framework's effectiveness and feasibility in real-world scenarios.

Conclusions:

  • The proposed framework offers a robust solution for cloud service selection by managing QoS complexities.
  • Integrating PCA and BWM provides a more accurate and user-centric approach to optimizing cloud service choices.
  • This methodology enhances the decision-making process for users seeking the best cloud services.