University of Oulu

T. Leppanen et al., "Edge-Based Microservices Architecture for Internet of Things: Mobility Analysis Case Study," 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, 2019, pp. 1-7.

Edge-based microservices architecture for Internet of Things : mobility analysis case study

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Author: Leppänen, Teemu1; Savaglio, Claudio2; Lovén, Lauri1;
Organizations: 1Center for Ubiquitous Computing, University of Oulu, Finland
2Department of Informatics, Modeling, Electronics and Systems, University of Calabria, Italy
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-03-25


In this paper, we describe how the microservices paradigm can be used to design and implement distributed edge services for Internet of Things applications. As a case study, traditionally monolithic user mobility analysis service is developed, with distributed and extendable microservices, for the standardized ETSI MEC system reference architecture. In each of the edge system three tiers, microservices implement the service logic with components for movement trace analysis, movement prediction and visualization of the results. The distributed service is implemented with Docker containers and evaluated on real-world settings with low capacity edge servers and real user mobility data. The results show that the edge promise of low latency can be met in such as implementation. The integration of a software development technology with a standardized edge system provides solid background for further development.

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Series: IEEE Global Communications Conference
ISSN: 2334-0983
ISSN-E: 2576-6813
ISSN-L: 2334-0983
ISBN: 978-1-7281-0962-6
ISBN Print: 978-1-7281-0963-3
Pages: 1 - 7
DOI: 10.1109/GLOBECOM38437.2019.9014273
Host publication: 2019 IEEE Global Communications Conference (GLOBECOM), December 9-14, Waikoloa, HI, USA
Conference: IEEE Global Communications Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: This research is financially supported by the AI-Enhanced Mobile Edge Computing -project, funded by the Future Makers program of Jane and Aatos Erkko Foundation and Technology Industries of Finland Centennial Foundation, and by the Academy of Finland 6Genesis Flagship (grant 318927).
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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