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Decision making for cloud service selection: a novel and hybrid MCDM approach

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Abstract

Cloud computing has emerged as a promising Internet technology enabling cloud users to access computing resources on-demand via the Internet in a “pay-as-you-use” fashion. Many cloud service providers (CSPs) have arisen over the last few years with similar features at varying prices and performance levels. With the rising number of CSPs, cloud customers face the challenge of choosing the right CSP that satisfies their Quality of Service requirements. However, it poses a major challenge: “How to evaluate a suitable CSP with high accuracy and consistency.” To address this challenge, this paper proposes a hybrid Multi-Criteria Decision Making methodology to aid the decision-maker to evaluate different cloud services. Specifically, a novel approach is introduced based on a comprehensive assessment that combines subjective and objective aspects. The comprehensive assessment results are utilized to rank the eligible CSPs based on their prioritized list. The simulation results are validated through a real-life case study which further justifies that the proposed approach provides better satisfaction degree from the user’s perspective and is efficient in terms of accuracy and reliability. Finally, we perform a sensitivity analysis to show the robustness and stability of our approach.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Netaji Subhas University of Technology, Dwarka Sector-3, New Delhi, Delhi, 110078, India

    Abhinav Tomar

  2. Department of Computer Science and Engineering, C V Raman Global University, Bhubaneswar, 752054, India

    Rakesh Ranjan Kumar

  3. Department of Computer Science and Engineering, Bennett University, Greater Noida, 201310, India

    Indrajeet Gupta

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  1. Abhinav Tomar
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  2. Rakesh Ranjan Kumar
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  3. Indrajeet Gupta
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Correspondence to Abhinav Tomar.

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Tomar, A., Kumar, R.R. & Gupta, I. Decision making for cloud service selection: a novel and hybrid MCDM approach. Cluster Comput 26, 3869–3887 (2023). https://doi.org/10.1007/s10586-022-03793-y

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  • DOI: https://doi.org/10.1007/s10586-022-03793-y

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