Academic paper summary

Chegini, H., Naha, R.K., Mahanti, A. and Thulasiraman, P., 2021. Process automation in an IoT–fog–cloud ecosystem: A survey and taxonomy. IoT, 2(1), pp.92-118.

https://mdpi-res.com/d_attachment/IoT/IoT-02-00006/article_deploy/IoT-02-00006-v2.pdf?version=1612923821

this is the academic paper I will summarize. the problem is that it is very long (23 pages) so this will be a summary of the first part of this academic paper :

there are various types of IoT components and applications in terms of data, software, hardware, and actors. Different types of information are introduced to the IoT application: local information (close to the IoT layer) and global information (close to the cloud layer). In terms of hardware, various hardware platforms collaborate for data processing in the ecosystem, such as computational resources, storing resources, disk resources, and network resources with multiple attributes. As for software, different programming codes exist. Communicating agents, small code scripts, data types, modular codes, compilers, Application Programming Interface (API), Operating Systems (OS), applications, and Machine Learning (ML) applications are all examples of various types of software codes. To summarize, the three main challenges in any IoT–Fog–Cloud are: (1) increasing Fog resiliency, (2) real-time processing of Big data, and (3) managing the heterogeneity. Tasks, algorithms, and functions need to be defined in a way to tackle these challenges. We also analyzed the number of publications in different digital libraries such as “Web of Science” and “Scopus” between the years 2010 and 2021 with chosen terms “context-aware systems”, “automation”, and “decision-making”. Figures 2 and 3 show the number of publications on IoT in combination with “context-aware systems”, “automation” and “decision-making”. These figures show that the noted topics are respected and considered for research. The number of publications in the respected area is increasing year by year. Automation in IoT is increasingly attracting the research community’s interest with a 43% growth in publications on automation in 2018 compared with 2017, and a 60% growth in 2017 compared with 2016. This shows that the topic of automation in the ecosystem is becoming very important and will attract more interest from the research community in the future compared to other research topics such as context-aware systems and decision-making

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