CloudAISim: A toolkit for modelling and simulation of modern applications in AI-driven cloud computing environments

被引:1
|
作者
Bhowmik A. [1 ]
Sannigrahi M. [1 ]
Chowdhury D. [2 ,3 ]
Dey A. [4 ]
Gill S.S. [5 ]
机构
[1] SeaTech School of Engineering, University of Toulon, Toulon
[2] Center for Application Research in India (CARIn), Carl Zeiss (Bangalore) India Pvt Ltd., Bangalore
[3] Dept of Electronics and Communication Engineering, IIIT Naya Raipur, Naya Raipur
[4] TCS Research and Innovation, Kolkata
[5] School of Electronic Engineering and Computer Science, Queen Mary University of London, London
关键词
Artificial intelligence; Cloud computing; CloudAISim; Explainable AI; Healthcare; Machine learning; Simulation;
D O I
10.1016/j.tbench.2024.100150
中图分类号
学科分类号
摘要
There is a very significant knowledge gap between Artificial Intelligence (AI) and a multitude of industries that exist in today's modern world. This is primarily attributable to the limited availability of resources and technical expertise. However, a major obstacle is that AI needs to be flexible enough to work in many different applications, utilising a wide variety of datasets through cloud computing. As a result, we developed a benchmark toolkit called CloudAISim to make use of the power of AI and cloud computing in order to satisfy the requirements of modern applications. The goal of this study is to come up with a strategy for building a bridge so that AI can be utilised in order to assist those who are not very knowledgeable about technological advancements. In addition, we modelled a healthcare application as a case study in order to verify the scientific reliability of the CloudAISim toolkit and simulated it in a cloud computing environment using Google Cloud Functions to increase its real-time efficiency. A non-expert-friendly interface built with an interactive web app has also been developed. Any user without any technical knowledge can operate the entire model, which has a 98% accuracy rate. The proposed use case is designed to put AI to work in the healthcare industry, but CloudAISim would be useful and adaptable for other applications in the future. © 2024 The Authors
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