A lightweight and cost effective edge intelligence architecture based on containerization technology

  • Mabrook Al-RakhamiEmail author
  • Abdu Gumaei
  • Mohammed Alsahli
  • Mohammad Mehedi Hassan
  • Atif Alamri
  • Antonio Guerrieri
  • Giancarlo Fortino
Part of the following topical collections:
  1. Special Issue on Smart Computing and Cyber Technology for Cyberization


The integration of Cloud computing and Internet of Things led to rapid growth in the edge computing field. This would not be achievable without combining the data centers’ managing systems with much more restrained technologies. One significantly effective and lightweight solution to this issue is presented by the Docker technology. It is able to manage virtualization process and can therefore be used to distribute, deploy and manage cloud and edge applications assigned into the clusters. In our study, this technology was represented by the Raspberry Pi devices, which are convenient thanks to their low cost, robust applicability and lightweight nature. Our application scenario focuses on identification of the human activities. In this paper, we suggest and evaluate an architecture on the basis of the distributed edge/cloud integration paradigm. We explain all of its advantages which lie in the combination of affordability and several other benefits provided by the fact that data processing is conducted by the edge devices instead of the central server. To recognize and identify human activity, the Regularized Extreme Leaning Machine (RELM) was engaged in our architecture. Our study presents detailed information about our use case scenario and the experimental simulation we performed.


Edge intelligence Edge computing Human activity recognition Docker Containers, regularized extreme leaning machine 



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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Research Chair of Pervasive and Mobile ComputingRiyadhSaudi Arabia
  2. 2.Information Systems Department, College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia
  3. 3.Computer Science Department, College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia
  4. 4.National Research Council of Italy, Institute for High Performance Computing and NetworkingCalabriaItaly
  5. 5.Department of Informatics, Modeling, Electronics and Systems (DIMES)University of CalabriaCalabriaItaly

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