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An empirical study for mitigating sustainable cloud computing challenges using ISM-ANN.

Hathal Salamah Alwageed1, Ismail Keshta2, Rafiq Ahmad Khan3

  • 1College of Computer and Information Sciences, Jouf University, Sakaka, Saudi Arabia.

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Summary
This summary is machine-generated.

This study addresses sustainable cloud computing challenges and offers a practical mitigation model. The proposed model helps organizations estimate sustainability efforts and provides a foundation for future research and development.

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Area of Science:

  • Computer Science
  • Environmental Science
  • Sociology

Background:

  • Cloud computing's growth, driven by AI, presents opportunities and threats to societal and environmental sustainability.
  • Unanswered questions exist regarding the environmental equilibrium and social sustainability impacts of widespread, interconnected computing systems.

Purpose of the Study:

  • To empirically investigate the ethical challenges and practices of cloud computing concerning sustainable development.
  • To identify and analyze sustainable cloud computing challenges (SCCCs) and develop a mitigation model (SCCCMM).

Main Methods:

  • Systematic literature review and questionnaire survey to identify 11 SCCCs and 66 practices.
  • Interpretive Structural Modeling (ISM) and Artificial Neural Networks (ANN) to analyze interrelationships between SCCCs.
  • Development and testing of the Sustainable Cloud Computing Challenges Mitigation Model (SCCCMM) using a case study.

Main Results:

  • Identified 11 SCCCs and 66 mitigation practices.
  • Developed the SCCCMM with four main categories: Requirements specification, Quality of Service (QoS) and Service Legal Agreement (SLA), Complexity and Cyber security, and Trust.
  • The SCCCMM effectively aids in estimating mitigation levels in sustainable cloud computing organizations.

Conclusions:

  • The SCCCMM is practical, user-friendly, and useful for organizations in cloud computing to enhance software product sustainability.
  • The model provides a strong foundation for researchers and practitioners to develop new sustainable cloud computing methods and tools.