Volume 23 , Issue 2 , PP: 32-41, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Mona Gharib 1 * , Florentin Smarandache 2 , Mona Mohamed 3
Doi: https://doi.org/10.54216/IJNS.230204
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.
Cloud Computing (ClC) , tree soft sets (TSSs) , Quality of Service (QoS) , Single Value Neutrosophic Sets (SVNSs) , Multi-Criteria Decision Making (MCDM)
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