An Application on Determining the Criteria for Selecting a Cloud Computing Service Provider
Keywords:
Cloud Computing, Multi-Criteria Decision Making, Fuzzy Pythagorean Entropy MethodAbstract
It is important to determine the strategies in the information policies implemented by businesses. In today's world, it is necessary to increase the level of competitiveness of enterprises by effectively determining strategies for cloud computing services. The corporate applications offered by cloud computing service providers are evaluated according to criteria such as network architecture, storage, end-user services, security models and pricing. The lack of a full understanding of the diversity and differences in the services offered by cloud computing service providers confronts users of cloud services with the problem of choosing the best cloud service provider. In this study, an application for selecting a cloud computing platform has been made. In the application, the fuzzy Pythagorean entropy method was used to weight the criteria for determining the strategy for cloud computing platforms of an enterprise operating in Gaziantep province.
References
Aksakal, E. (2021). Kayak Ekipman Seçiminde Dikkate Alınacak Kriterlerin Pisagor Bulanık Entropi Yöntemi ile Değerlendirilmesi. Bulanık Çok Kriterli Karar Verme Yöntemleri (s. 187-201). içinde Ankara: Nobel Akademik Yayıncılık.
Al-Sayyed, R. M., Hijawi, W. A., Bashiti, A. M., & brahim AlJarah, N. O. (2019). An Investigation of Microsoft Azure and Amazon Web Services from Users’ Perspectives. International Journal of Emerging Technologies in Learning, 14(10).
Avşar, İ. İ. (2023). TÜRK HAVACILIK SEKTÖRÜNÜN ÇOK KRİTERLİ KARAR VERME YÖNTEMLERİYLE DEĞERLENDİRİLMESİ: 2002-2022 DÖNEMİ. Bingöl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(26), 153-169. https://doi.org/10.29029/busbed.1295361.
Borra, P. (2024). COMPARISON AND ANALYSIS OF LEADING CLOUD SERVICE PROVIDERS (AWS, AZURE AND GCP). International Journal of Advanced Research in Engineering and Technology (IJARET), 266-278.
Boutkhoum, O., Hanine, M., Agouti, T., & Tikniouine, A. (2016). Selection problem of cloud solution for big data accessing: fuzzy AHP-PROMETHEE as a proposed methodology. Journal of Digital Information Management, 368382.
Çelik, K. (2021). Bulut Bilişim Teknolojileri. Bartın Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 436-450. DOI: 10.47129/bartiniibf.1019898.
Davutoğlu, N. A. (2022). TEKNO YÖNETİM ALT YAPISININ GİZİLGÜCÜ OLAN BULUT BİLİŞİM YÖNETİM SİSTEMİNE DETERMİNİST BİR YAKLAŞIM. Premium e-Journal of Social Science (PEJOSS), 6(22),, 321-331.
Deringöz, A., Danışan, T., & Eren, T. (2022). Covid-19 Takibinde Giyilebilir Sağlık Teknolojilerinin ÇKKV Yöntemleri ile Değerlendirilmesi. Politeknik Dergisi, 533–543.
Dokuz, A. Ş., & Çelik, M. (2017). Bulut bilişim sistemlerinde verinin farkli boyutlari üzerine derleme. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 6(2),, 316-338.
Ecer, F., & Pamucar, D. (2020). Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo’B) multi-criteria model. Journal of cleaner production, 121981.
Ersöz, F., & Kabak, M. (2010). SAVUNMA SANAYİ UYGULAMALARINDA ÇOK KRİTERLİ KARAR VERME YÖNTEMLERİNİN LİTERATÜR ARAŞTIRMASI. Savunma Bilimleri Dergisi, vol. 9, no. 1,, 97–125, 2010, doi: 10.17134/sbd.85950. .
Garg, R. (2022). MCDM-Based Parametric Selection of Cloud Deployment Models for an Academic Organization. IEEE Transactions on Cloud Computing, vol. 10, no. 2, 863-871.
Gupta, B., Mittal, P., & Mufti, T. (2021). A Review on Amazon Web Service (AWS), Microsoft Azure & Google Cloud Platform (GCP) Services. Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development. New Delhi, India: EAI.
Gyani, J., Ahmed, A., & Haq, M. A. (2022). MCDM and Various Prioritization Methods in AHP for CSS: A Comprehensive Review. in IEEE Access, vol. 10,, 33492-33511.
Haseki, M. İ., & Avşar, İ. İ. (2023). AVRUPA BİRLİĞİ VE SEÇİLİ ÜLKELERİNİN TEKNOLOJİ ÜRETİM ODAKLI VERİLERİNİN ENTROPİ VE GRİ İLİŞKİLER ANALİZ MODELLERİYLE İNCELENMESİ. Uluslararası İktisadi Ve İdari İncelemeler Dergisi(39), , 154-169.
Koşar, O., & Atak, M. (2023). Bulut Bilişim Sanal Sunucu Ürün Seçiminde Çok Kriterli Bir Karar Destek Modeli. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 38(4), , 939-953. https://doi.org/10.21605/cukurovaumfd.1410269.
Kumar, R. R., Kumari, B., & Kumar, C. (2021 ). CCS-OSSR: A framework based on Hybrid MCDM for Optimal Service Selection and Ranking of Cloud Computing Services. Cluster Computing , 24:867–883.
Neeraj, Goraya, M. S., & Singh, D. (2021). A comparative analysis of prominently used MCDM methods in cloud environment. The Journal of Supercomputing, 3422–3449.
Ölç, Y., & Göçer, F. (2024). Pisagor Bulanık Küme Ortamında Yenilenebilir Enerji Kaynağı Seçimi. ALKÜ Fen Bilimleri Dergisi, 96-115.
Padyana, U. K., Rai, H. P., Ogeti, P., Fadnavis, N. S., & Patil, G. B. (2020). Server less Architectures in Cloud Computing: Evaluating Benefits and Drawbacks. INNOVATIVE RESEARCH THOUGHTS.
Rehman, Z. u., Hussain, O. K., & Hussain, F. K. (2012). Iaas Cloud Selection using MCDM Methods. IEEE Ninth international conference on e-business engineering (s. 246-251). IEEE.
Şeker, Ş., & Aydın, N. (2020). Hydrogen production facility location selection for Black Sea using entropy based TOPSIS under IVPF environment. International Journal of Hydrogen Energy 45(32), 15855-15868.
Yager, R. R. (2013). Pythagorean fuzzy subsets. 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS),IEEE, (s. 57–61). pp. 57–61. doi: 10.1109/IFSA-NAFIPS.2013.6608375.
Yaykaşlı, M., & Ecemiş, O. (2018). OTOMOBİL SATIN ALMA PROBLEMİNDE ÇOK KRİTERLİ KARAR VERME YÖNTEMLERİYLE BİR UYGULAMA. Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 10(26), 967-987. https://doi.org/10.20875/makusobed.500167.
Yıldız, Ö. R. (2009). BİLİŞİM DÜNYASININ YENİ MODELİ: BULUT BİLİŞİM CLOUD COMPUTING VE DENETİM. Sayıştay Dergisi, , (74), 5-23.
Youssef, A. E. (2020). An Integrated MCDM Approach for Cloud Service Selection Based on TOPSIS and BWM. in IEEE Access,, 71851-71865.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Journal of International Economics, Finance and Trade
This work is licensed under a Creative Commons Attribution 4.0 International License.