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A framework for evaluating cloud computing services using AHP and TOPSIS approaches with interval valued spherical fuzzy sets

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Abstract

The interaction of multi criteria decision making for deciding optimal decision among the entirety of the likely other alternatives. The availability of numerous amount of cloud services make it challenging for decision makers to select a cloud service according to their non-functional requirements as a number of criteria has to be included during selection of cloud services. The amalgamation of analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) has driven analysts to incorporate the blend with various augmentations of fuzzy sets. Extension of fuzzy set, the newly created 3-D spherical fuzzy set (SFS), is viable in dealing with vulnerability and evaluating expert decisions. In this paper, we have proposed general framework by combining AHP and TOPSIS methods under the dimensions of SFSs. SFAHP is employed to figure the importance of criteria and then these criteria weights used in IVSFTOPSIS (interval valued spherical fuzzy TOPSIS) to track down the ranking position of cloud service providers. This study addresses five different alternatives to six conflicting benchmarks by three decision makers. Sensitivity analysis is also conducted to highlight the reliability of proposed method.

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Data Availability

The datasets analysed during the current study are available in the [github] repository, [https://qwsdata.github.io/] and all the data generated during this are included in this paper.

References

  1. Abdel-Basset, M., Mohamed, M., Chang, V.: NMCDA: a framework for evaluating cloud computing services. Future Gener. Comput. Syst. 86, 12–29 (2018)

    Article  Google Scholar 

  2. Monika, Sangwan, O.P.: Quality evaluation of cloud services using MCDM techniques: a comparative analysis. In: Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021), pp. 371–383. Springer International Publishing, Cham (2022)

  3. Zadeh, L.A.: Fuzzy sets. In: Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers by Lotfi A Zadeh, pp. 394–432. World Scientific (1996)

  4. Mohandes, S.R., Sadeghi, H., Mahdiyar, A., Durdyev, S., Banaitis, A., Yahya, K., Ismail, S.: Assessing construction labours’ safety level: a fuzzy MCDM approach. J. Civ. Eng. Manag. 26(2), 175–188 (2020)

    Article  Google Scholar 

  5. Atanassov, K.T.: Intuitionistic fuzzy sets. In: Intuitionistic Fuzzy Sets, pp. 1–137. Springer, Cham (1999)

  6. Parveen, N., Kamble, P.N.: An extension of TOPSIS for group decision making in intuitionistic fuzzy environment. Math. Found. Comput. 4(1), 61 (2021)

    Article  MATH  Google Scholar 

  7. Smarandache, F.: Neutrosophic Logic and Set. Citeseer (1995). https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.596.7590

  8. Saqlain, M., Jafar, M.N., Riaz, M.: A new approach of neutrosophic soft set with generalized fuzzy TOPSIS in application of smart phone selection. Neutrosophic Sets Syst. 32, 307–316 (2020)

    Google Scholar 

  9. Yager, R.R.: Pythagorean fuzzy subsets. In: 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), pp. 57–61. IEEE (2013)

  10. Kutlu Gündoğdu, F., Kahraman, C.: Spherical fuzzy sets and spherical fuzzy TOPSIS method. J. Intell. Fuzzy Syst. 36(1), 337–352 (2019)

    Article  MATH  Google Scholar 

  11. Kutlu Gündoğdu, F., Kahraman, C.: A novel VIKOR method using spherical fuzzy sets and its application to warehouse site selection. J. Intell. Fuzzy Syst. 37(1), 1197–1211 (2019)

    Article  Google Scholar 

  12. Atanassov, K.T.: Interval valued intuitionistic fuzzy sets. In: Intuitionistic Fuzzy Sets, pp. 139–177. Springer, Cham (1999)

  13. Gündoğdu, F.K., Kahraman, C.: A novel fuzzy TOPSIS method using emerging interval-valued spherical fuzzy sets. Eng. Appl. Artif. Intell. 85, 307–323 (2019)

    Article  Google Scholar 

  14. Hwang, C.L., Yoon, K.: Methods for multiple attribute decision making. In: Multiple Attribute Decision Making, pp. 58–191. Springer, Berlin (1981)

  15. Yasmin, M., Tatoglu, E., Kilic, H.S., Zaim, S., Delen, D.: Big data analytics capabilities and firm performance: an integrated MCDM approach. J. Bus. Res. 114, 1–15 (2020)

    Article  Google Scholar 

  16. Büyüközkan, G., Göçer, F., Feyzioğlu, O.: Cloud computing technology selection based on interval-valued intuitionistic fuzzy MCDM methods. Soft Comput. 22(15), 5091–5114 (2018)

    Article  Google Scholar 

  17. Bolturk, E., Kahraman, C.: A novel interval-valued neutrosophic AHP with cosine similarity measure. Soft Comput. 22(15), 4941–4958 (2018)

    Article  Google Scholar 

  18. Sharma, H., Tandon, A., Kapur, P., Aggarwal, A.G.: Ranking hotels using aspect ratings based sentiment classification and interval-valued neutrosophic TOPSIS. Int. J. Syst. Assur. Eng. Manag. 10(5), 973–983 (2019)

    Article  Google Scholar 

  19. Tian, C., Peng, J.: An integrated picture fuzzy ANP-TODIM multi-criteria decision-making approach for tourism attraction recommendation. Technol. Econ. Dev. Econ. 26(2), 331–354 (2020)

    Article  Google Scholar 

  20. Li, J., Chen, Q., Niu, L.l., Wang, Z.X.: An ORESTE approach for multi-criteria decision-making with probabilistic hesitant fuzzy information. Int. J. Mach. Learn. Cybern. 11(7), 1591–1609 (2020)

  21. Bakioglu, G., Atahan, A.O.: AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles. Appl. Soft Comput. 99, 106948 (2021)

    Article  Google Scholar 

  22. Yücesan, M., et al.: Green supplier selection for plastic industry using integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS. J. Bus. Res. Turk 11(1), 26–41 (2019)

    Article  Google Scholar 

  23. Aghamohagheghi, M., Hashemi, S., Tavakkoli-Moghaddam, R.: An advanced decision support framework to assess sustainable transport projects using a new uncertainty modeling tool: interval-valued Pythagorean trapezoidal fuzzy numbers. Iran. J. Fuzzy Syst. 18(1), 53–73 (2021)

    MathSciNet  MATH  Google Scholar 

  24. Kumar, R.R., Shameem, M., Kumar, C.: A computational framework for ranking prediction of cloud services under fuzzy environment. Enterp. Inf. Syst. 16(1), 167–187 (2022)

    Article  Google Scholar 

  25. Zhou, T., Chen, Z., Ming, X.: A novel hesitant fuzzy linguistic hybrid cloud model and extended best-worst method for multicriteria decision making. Int. J. Intell. Syst. 37(1), 596–624 (2022)

    Article  Google Scholar 

  26. Thasni, T., Kalaiarasan, C., Venkatesh, K.: Service measurement index-based cloud service selection using order preference by similarity to ideal solution based on intuitionistic fuzzy values. In: 3rd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing, pp. 225–238. Springer (2022)

  27. Ullah, K., Hassan, N., Mahmood, T., Jan, N., Hassan, M.: Evaluation of investment policy based on multi-attribute decision-making using interval valued t-spherical fuzzy aggregation operators. Symmetry 11(3), 357 (2019)

    Article  Google Scholar 

  28. Duleba, S., Kutlu Gündoğdu, F., Moslem, S.: Interval-valued spherical fuzzy analytic hierarchy process method to evaluate public transportation development. Informatica 32(4), 661–686 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  29. Candan, G., Cengiz Toklu, M.: Sustainable industrialization performance evaluation of European union countries: an integrated spherical fuzzy analytic hierarchy process and grey relational analysis approach. Int. J. Sustain. Dev. World Ecol. 29(5), 387–400 (2022)

    Article  Google Scholar 

  30. Omerali, M., Kaya, T.: Augmented reality application selection framework using spherical fuzzy COPRAS multi criteria decision making. Cogent Eng. 9(1), 2020610 (2022)

    Article  Google Scholar 

  31. Tsai, W.L.: Constructing assessment indicators for enterprises employing cloud IaaS. Asia Pac. Manag. Rev. 26(1), 23–29 (2021)

    Google Scholar 

  32. Tabassum, N., Alyas, T., Hamid, M., Saleem, M., Malik, S., Zahra, S.B.: QoS based cloud security evaluation using neuro fuzzy model. CMC 70(1), 1127–1140 (2022)

    Article  Google Scholar 

  33. Arun Kumar, B., Komala, R.: The blockchain-based decentralized approaches for cloud computing to offer enhanced quality of service in terms of privacy preservation and security: a review. Int. J. Comput. Sci. Netw. Secur. 21(4), 115–122 (2021)

    Google Scholar 

  34. Nguyen, V.T., Hai, N.H., Lan, N.T.K., et al.: Spherical fuzzy multicriteria decision-making model for wind turbine supplier selection in a renewable energy project. Energies 15(3), 713 (2022)

    Article  Google Scholar 

  35. Kutlu Gündoğdu, F., Kahraman, C.: Properties and arithmetic operations of spherical fuzzy sets. In: Decision Making with Spherical Fuzzy Sets, pp. 3–25. Springer, Cham (2021)

  36. Kahraman, C., Kutlu Gündoğdu, F.: From 1d to 3d membership: spherical fuzzy sets. In: BOS/SOR2018 Conference. Warsaw (2018)

  37. Lathamaheswari, M., Nagarajan, D., Garg, H., Kavikumar, J.: Interval valued spherical fuzzy aggregation operators and their application in decision making problem. In: Decision Making with Spherical Fuzzy Sets, pp. 27–51. Springer, Cham (2021)

  38. Ullah, K., Garg, H., Mahmood, T., Jan, N., Ali, Z.: Correlation coefficients for t-spherical fuzzy sets and their applications in clustering and multi-attribute decision making. Soft Comput. 24(3), 1647–1659 (2020)

    Article  MATH  Google Scholar 

  39. Saaty, R.W.: The analytic hierarchy process—what it is and how it is used. Math. Model. 9(3–5), 161–176 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  40. Sharaf, I.M.: Global supplier selection with spherical fuzzy analytic hierarchy process. In: Decision Making with Spherical Fuzzy Sets, pp. 323–348. Springer, Cham (2021)

  41. Aydın, S., Gündoğdu, F.K.: Interval-valued spherical fuzzy MULTIMOORA method and its application to industry 4.0. In: Decision Making with Spherical Fuzzy Sets, pp. 295–322. Springer, Cham (2021)

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  1. Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India

    Monika & Om Prakash Sangwan

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  1. Monika
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  2. Om Prakash Sangwan
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by [M]. The first draft of the manuscript was written by [M] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Monika.

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Monika, Sangwan, O.P. A framework for evaluating cloud computing services using AHP and TOPSIS approaches with interval valued spherical fuzzy sets. Cluster Comput 25, 4383–4396 (2022). https://doi.org/10.1007/s10586-022-03679-z

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  • DOI: https://doi.org/10.1007/s10586-022-03679-z

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