International Journal of Neutrosophic Science

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https://doi.org/10.54216/IJNS

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2690-6805ISSN (Online) 2692-6148ISSN (Print)

Volume 23 , Issue 2 , PP: 32-41, 2024 | Cite this article as | XML | Html | PDF | Full Length Article

CSsEv: Modelling QoS Metrics in Tree Soft Toward Cloud Services Evaluator based on Uncertainty Environment

Mona Gharib 1 * , Florentin Smarandache 2 , Mona Mohamed 3

  • 1 Department of Mathematics, Faculty of Science, Zagazig University, 44519 Zagazig, Egypt - (monagharib@zu.edu.eg)
  • 2 University of New Mexico, 705 Gurley Ave., Gallup, NM 87301, USA - (smarand@unm.edu)
  • 3 Higher Technological Institute, 10th of Ramadan City 44629, Egypt - (mona.fouad@hti.edu.eg)
  • Doi: https://doi.org/10.54216/IJNS.230204

    Received: June 21, 2023 Revised: October 19, 2023 Accepted: November 19, 2023
    Abstract

    Cloud computing (ClC) has become a more popular computer paradigm in the preceding few years. Quality of Service (QoS) is becoming a crucial issue in service alteration because of the rapid growth in the number of cloud services. When evaluating cloud service functioning using several performance measures, the issue becomes more complex and non-trivial. It is therefore quite difficult and crucial for consumers to choose the best cloud service. The user's choices are provided in a quantifiable manner in the current methods for choosing cloud services. Hence, this study attempts to achieve this objective through construction. decision-making framework so-called cloud services evaluator (CSsEv). The main indicator and its sub-indicators are formed as nodes at levels(n) in tree soft sets (TSSs). Thereafter Single Value Neutrosophic Sets (SVNSs) as branch of neutrosophic sets which conjunction with the Multi-Criteria Decision Making (MCDM) technique to facilitate analysis and evaluation process for the available Cloud services providers. Hence, entropy is employed to obtain indicators and sub_indicators’ weights and Complex Proportional Assessment utilizes these weights to facilitate the decision process of selecting optimal ClSPs.

    Keywords :

    Cloud Computing (ClC) , tree soft sets (TSSs) , Quality of Service (QoS) , Single Value Neutrosophic Sets (SVNSs) , Multi-Criteria Decision Making (MCDM)

    References

    [1]        Tomar, A., Kumar, R. R., & Gupta, I. (2023). Decision making for cloud service selection: a novel and hybrid MCDM approach. Cluster computing, 26(6), 3869–3887. DOI:10.1007/s10586-022-03793-y

    [2]        Cloud, H. (2011). The nist definition of cloud computing. National institute of science and technology, special publication, 800(2011), 145.

    [3]        Kumar, A., Sah, B., Singh, A. R., Deng, Y., He, X., Kumar, P., & Bansal, R. C. (2017). A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and sustainable energy reviews, 69, 596–609.

    [4]        Raut, R. D., Priyadarshinee, P., Gardas, B. B., & Jha, M. K. (2018). Analyzing the factors influencing cloud computing adoption using three stage hybrid SEM-ANN-ISM (SEANIS) approach. Technological forecasting and social change, 134, 98–123.

    [5]        Büyüközkan, G., Uztürk, D., & Maden, A. (2023). Influential factor analysis for cloud computing technology service provider. Technological forecasting and social change, 192(December 2022). DOI:10.1016/j.techfore.2023.122531

    [6]        Kumar Tiwari, R., & Kumar, R. (2022). A framework for prioritizing cloud services in neutrosophic environment. Journal of king saud university - computer and information sciences, 34(6), 3151–3166. DOI:10.1016/j.jksuci.2020.05.009

    [7]        Ardagna, D., Casale, G., Ciavotta, M., Pérez, J. F., & Wang, W. (2014). Quality-of-service in cloud computing: modeling techniques and their applications. Journal of internet services and applications, 5(1), 1–17.

    [8]        Saha, M., Panda, S. K., & Panigrahi, S. (2022). A Survey on Applications of Multi-Attribute Decision Making Algorithms in Cloud Computing. ECS transactions, 107(1), 12887–12900. DOI:10.1149/10701.12887ecst

    [9]        Karabasevic, D., Popovic, G., Stanujkic, D., Maksimovic, M., & Sava, C. (2019). An approach for hotel type selection based on the single-valued intuitionistic fuzzy numbers. Int. rev, 1, 7.

    [10]      Abdel-Monem, A., Mohamed, S. S., & Aziz, A. S. (2023). A Multi-Criteria Decision Making Methodology for Assessment Performance of Electrocoagulation System. Multicriteria algorithms with applications, 1(1), 19–30.

    [11]      Kumar, R. R., Tomar, A., Shameem, M., & Alam, M. N. (2022). OPTCLOUD: An Optimal Cloud Service Selection Framework Using QoS Correlation Lens. Computational intelligence and neuroscience, 2022. DOI:10.1155/2022/2019485

    [12]      Petrovic, I., & Kankaras, M. (2020). A hybridized IT2FS-DEMATEL-AHP-TOPSIS multicriteria decision making approach: Case study of selection and evaluation of criteria for determination of air traffic control radar position. Decision making: applications in management and engineering, 3(1), 146–164.

    [13]      Smarandache, F., & Abdel-Basset, M. (2021). Neutrosophic Operational Research: Methods and Applications. , Neutrosophic Operational Research: Methods and Applications.

    [14]      Atanassov, K. T., & Atanassov, K. T. (1999). Interval valued intuitionistic fuzzy sets. Intuitionistic fuzzy sets: theory and applications, 139–177.

    [15]      Smarandache, F. (1999). A unifying field in Logics: Neutrosophic Logic. In Philosophy (pp. 1–141). American Research Press.

    [16]      Smarandache, F. (2023). New Types of Soft Sets: HyperSoft Set, IndetermSoft Set, IndetermHyperSoft Set, and TreeSoft Set. International journal of neutrosophic science, 20(4), 58–64. DOI:10.54216/IJNS.200404

    [17]      Garg, S. K., Versteeg, S., & Buyya, R. (2013). A framework for ranking of cloud computing services. Future generation computer systems, 29(4), 1012–1023.

    [18]      Mousavi-Nasab, S. H., & Sotoudeh-Anvari, A. (2017). A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials & design, 121, 237–253.

    [19]      Jahan, A., Ismail, M. Y., Sapuan, S. M., & Mustapha, F. (2010). Material screening and choosing methods–a review. Materials & design, 31(2), 696–705.

    [20]      Shameem, M., Kumar, R. R., Nadeem, M., & Khan, A. A. (2020). Taxonomical classification of barriers for scaling agile methods in global software development environment using fuzzy analytic hierarchy process. Applied soft computing, 90, 106122.

    [21]      Mohamed, M. (2023). Toward Smart Logistics: Hybrization of Intelligence Techniques of Machine Learning and Multi-Criteria Decision-Making in Logistics 5.0. Multicriteria algorithms with applications, 1(1), 42–57.

    [22]      Liu, F., Aiwu, G., Lukovac, V., & Vukic, M. (2018). A multicriteria model for the selection of the transport service provider: A single valued neutrosophic DEMATEL multicriteria model. Decision making: applications in management and engineering, 1(2), 121–130.

    [23]      Karaşan, A., Boltürk, E., & Kahraman, C. (2019). A novel neutrosophic CODAS method: Selection among wind energy plant locations. Journal of intelligent & fuzzy systems, 36(2), 1491–1504.

    [24]      Ismail, M. M., Ahmed, Z., Abdel-Gawad, A. F., & Mohamed, M. (2024). Toward Supply Chain 5.0: An Integrated Multi-Criteria Decision-Making Models for Sustainable and Resilience Enterprise. Decision making: applications in management and engineering, 7(1), 160–186.

    [25]      Hussein, G. S., Zaied, A. N. H., & Mohamed, M. (2023). ADM: Appraiser Decision Model for Empowering Industry 5.0-Driven Manufacturers toward Sustainability and Optimization: A Case Study. Neutrosophic systems with applications, 11, 22–30.

    [26]      Al-baker, S. F., & Mohamed, M. (2024). Exploring the Influences of Metaverse on Education Based on the Neutrosophic Appraiser Model, 23(01), 134–145.

    [27]      Büyüközkan, G., Uztürk, D., & Maden, A. (2023). Influential factor analysis for cloud computing technology service provider. Technological forecasting and social change, 192, 122531.

    [28]      Mohamed, M. (2023). Financial Risks Appraisal based on Dynamic Appraisal Framework. Neutrosophic and information fusion, 2(1), 50–58. DOI:10.54216/nif.020104

    Cite This Article As :
    Gharib, Mona. , Smarandache, Florentin. , Mohamed, Mona. CSsEv: Modelling QoS Metrics in Tree Soft Toward Cloud Services Evaluator based on Uncertainty Environment. International Journal of Neutrosophic Science, vol. , no. , 2024, pp. 32-41. DOI: https://doi.org/10.54216/IJNS.230204
    Gharib, M. Smarandache, F. Mohamed, M. (2024). CSsEv: Modelling QoS Metrics in Tree Soft Toward Cloud Services Evaluator based on Uncertainty Environment. International Journal of Neutrosophic Science, (), 32-41. DOI: https://doi.org/10.54216/IJNS.230204
    Gharib, Mona. Smarandache, Florentin. Mohamed, Mona. CSsEv: Modelling QoS Metrics in Tree Soft Toward Cloud Services Evaluator based on Uncertainty Environment. International Journal of Neutrosophic Science , no. (2024): 32-41. DOI: https://doi.org/10.54216/IJNS.230204
    Gharib, M. , Smarandache, F. , Mohamed, M. (2024) . CSsEv: Modelling QoS Metrics in Tree Soft Toward Cloud Services Evaluator based on Uncertainty Environment. International Journal of Neutrosophic Science , () , 32-41 . DOI: https://doi.org/10.54216/IJNS.230204
    Gharib M. , Smarandache F. , Mohamed M. [2024]. CSsEv: Modelling QoS Metrics in Tree Soft Toward Cloud Services Evaluator based on Uncertainty Environment. International Journal of Neutrosophic Science. (): 32-41. DOI: https://doi.org/10.54216/IJNS.230204
    Gharib, M. Smarandache, F. Mohamed, M. "CSsEv: Modelling QoS Metrics in Tree Soft Toward Cloud Services Evaluator based on Uncertainty Environment," International Journal of Neutrosophic Science, vol. , no. , pp. 32-41, 2024. DOI: https://doi.org/10.54216/IJNS.230204