Dynamic Resource Provisioning of a Scalable E2E Network Slicing Orchestration System
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Afolabi, Ibrahim; Prados Garzón, Jonathan; Bagaa, Miloud; Taleb, Tarik; Ameigeiras Gutiérrez, Pablo JoséEditorial
Institute of Electrical and Electronics Engineers (IEEE)
Materia
Network slicing Dimensioning Orchestration 5G Queuing model Analytical model Auto-scaling
Date
2019-07Referencia bibliográfica
I. Afolabi, J. Prados-Garzon, M. Bagaa, T. Taleb and P. Ameigeiras, "Dynamic Resource Provisioning of a Scalable E2E Network Slicing Orchestration System," in IEEE Transactions on Mobile Computing, vol. 19, no. 11, pp. 2594-2608, 1 Nov. 2020, doi: 10.1109/TMC.2019.2930059.
Sponsorship
This research work is partially supported by the European Union’s Horizon 2020 research and innovation program under the 5G!Pagoda project, the MATILDA project and the Academy of Finland 6Genesis project with grant agreement No. 723172, No. 761898 and No. 318927, respectively. It was also partially funded by the Academy of Finland Project CSN - under Grant Agreement 311654 and the Spanish Ministry of Education, Culture and Sport (FPU Grant 13/04833), and the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (TEC2016-76795-C6- 4-R).Abstract
Network slicing allows different applications and
network services to be deployed on virtualized resources running
on a common underlying physical infrastructure. Developing
a scalable system for the orchestration of end-to-end (E2E)
mobile network slices requires careful planning and very reliable
algorithms. In this paper, we propose a novel E2E Network
Slicing Orchestration System (NSOS) and a Dynamic Auto-
Scaling Algorithm (DASA) for it. Our NSOS relies strongly on
the foundation of a hierarchical architecture that incorporates
dedicated entities per domain to manage every segment of the
mobile network from the access, to the transport and core
network part for a scalable orchestration of federated network
slices. The DASA enables the NSOS to autonomously adapt
its resources to changes in the demand for slice orchestration
requests (SORs) while enforcing a given mean overall time taken
by the NSOS to process any SOR. The proposed DASA includes
both proactive and reactive resource provisioning techniques).
The proposed resource dimensioning heuristic algorithm of the
DASA is based on a queuing model for the NSOS, which consists
of an open network of G/G/m queues. Finally, we validate the
proper operation and evaluate the performance of our DASA
solution for the NSOS by means of system-level simulations.