International Journal of Electronics and Microcircuits
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P-ISSN: 2708-4493, E-ISSN: 2708-4507

2024, Vol. 4, Issue 1, Part A


AI cloud system sustainability analysis using hybrid MCDM model


Author(s): Sweta S Munnoli and Devi Venkatesh Gowtham

Abstract: Nowadays, more and more of our daily lives are dependent on cloud computing. It powers everything from infrastructure to social media. As a representation of society's reliance and interaction with automated computing systems, the ability to handle changing loads and usage is crucial for such a system to satisfy Quality of Service (QoS) assurances. To meet the demands of creating computer applications, a number of conceptual technologies have been integrated to provide these systems. Identifying the key technologies that will enable future uses is crucial for understanding the system's present and potential difficulties. In this research, we look at three emerging AI paradigms and try to predict how they will affect cloud computing in the future. In addition, we highlight the key technologies that are driving these paradigm shifts and bring in industry leaders to talk about where cloud computing is now and where it's going. Lastly, we proposed a cloud futurology conceptual model to investigate how new concepts and technologies impact cloud computing's expansion. The purpose of this research is to determine what factors are most important for the IT sector to consider when building an AI cloud system that can last. This was accomplished through the development and implementation of an AHP-Entropyintegrated hybrid multi-criteria decision-making (MCDM) model. Parameter importance was determined using the analytic hierarchy process (AHP), and parameter interrelationships were established using interpretive structural modeling (ISM). To choose the best cloud solution for managing big data projects in a group decision-making setting, we present a hybrid entropy method-AHP approach in this research. By utilizing usability analysis with the suggested hybrid AHP-Entropy method, we were able to compile decision makers' individual opinions regarding the relative importance of different criteria and alternatives.

Pages: 34-37 | Views: 6 | Downloads: 4

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International Journal of Electronics and Microcircuits
How to cite this article:
Sweta S Munnoli, Devi Venkatesh Gowtham. AI cloud system sustainability analysis using hybrid MCDM model. Int J Electron Microcircuits 2024;4(1):34-37.
International Journal of Electronics and Microcircuits
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