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Ren, Yi 
ORCID: https://orcid.org/0000-0001-7423-6719, Phung-Duc, Tuan, Chen, Jyh-Cheng and Yu, Zheng-Wei
(2017)
Dynamic Auto Scaling Algorithm (DASA) for 5G Mobile Networks.
In:
2016 IEEE Global Communications Conference (GLOBECOM).
The Institute of Electrical and Electronics Engineers (IEEE), USA, pp. 1-6.
ISBN 978-1-5090-1329-6
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Abstract
Network Function Virtualization (NFV) enables mobile operators to virtualize their network entities as Virtualized Network Functions (VNFs), offering fine-grained on-demand network capabilities. VNFs can be dynamically scale-in/out to meet the performance desire and other dynamic behaviors. However, designing the auto-scaling algorithm for desired characteristics with low operation cost and low latency, while considering the existing capacity of legacy network equipment, is not a trivial task. In this paper, we propose a VNF Dynamic Auto Scaling Algorithm (DASA) considering the tradeoff between performance and operation cost. We develop an analytical model to quantify the tradeoff and validate the analysis through extensive simulations. The results show that the DASA can significantly reduce operation cost given the latency upper-bound. Moreover, the models provide a quick way to evaluate the cost- performance tradeoff and system design without wide deployment, which can save cost and time.
| Item Type: | Book Section |
|---|---|
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Data Science and AI |
| Related URLs: | |
| Depositing User: | Pure Connector |
| Date Deposited: | 26 Jan 2018 15:30 |
| Last Modified: | 11 Dec 2024 01:12 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/66105 |
| DOI: | 10.1109/GLOCOM.2016.7841759 |
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