University of Oulu

L. Lovén et al., "Scaling up an Edge Server Deployment," 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Austin, TX, USA, 2020, pp. 1-7, doi: 10.1109/PerComWorkshops48775.2020.9156204

Scaling up an edge server deployment

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Author: Lovén, Lauri1; Lähderanta, Tero2; Ruha, Leena2;
Organizations: 1Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
2Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 5 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-11-03


In this article, we study the scaling up of edge computing deployments. In edge computing, deployments are scaled up by adding more computational capacity atop the initial deployment, as deployment budgets allow. However, without careful consideration, adding new servers may not improve proximity to the mobile users, crucial for the Quality of Experience of users and the Quality of Service of the network operators. In this paper, we propose a novel method for scaling up an edge computing deployment by selecting the optimal number of new edge servers and their placement, and re-allocating access points optimally to the old and new edge servers. The algorithm is evaluated with two scenarios, using data on a real-world large-scale wireless network deployment. The evaluation shows that the proposed method is stable on a real city-scale deployment, resulting in optimized Quality of Service for the network operator.

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ISBN: 978-1-7281-4717-8
ISBN Print: 978-1-7281-4716-1
Pages: 1 - 7
Article number: 9156204
DOI: 10.1109/PerComWorkshops48775.2020.9156204
Host publication: 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020
Conference: IEEE International Conference on Pervasive Computing and Communications Workshops
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
111 Mathematics
113 Computer and information sciences
Funding: This research is supported by Academy of Finland 6Genesis Flagship (grant 318927), the Infotech Oulu research institute, the Future Makers program of the Jane and Aatos Erkko Foundation and the Technology Industries of Finland Centennial Foundation, by Academy of Finland Profi 5 funding for mathematics and AI: data insight for high-dimensional dynamics, and by the personal grant for Lauri Lovén on Edgenative AI research by the Tauno T¨onning foundation.
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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