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Dynamic Slicing Approach for Multi-Tenant 5G Transport Networks
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS.
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2018 (English)In: Journal of Optical Communications and Networking, ISSN 1943-0620, E-ISSN 1943-0639, Vol. 10, no 1, p. A77-A90Article in journal (Refereed) Published
Abstract [en]

Software defined networking allows network providers to share their physical network (PN) among multiple tenants by means of network slicing, where several virtual networks (VNs) are provisioned on top of the physical one. In this scenario, PN resource utilization can be improved by introducing advanced orchestration functionalities that can intelligently assign and redistribute resources among the slices of different tenants according to the temporal variation of the VN resource requirements. This is a concept known as dynamic slicing. This paper presents a solution for the dynamic slicing problem in terms of both mixed integer linear programming formulations and heuristic algorithms. The benefits of dynamic slicing are compared against static slicing, i.e., an approach without intelligent adaptation of the amount of resources allocated to each VN. Simulation results show that dynamic slicing can reduce the VN rejection probability by more than 1 order of magnitude compared to static slicing. This can help network providers accept more VNs into their infrastructure and potentially increase their revenues. The benefits of dynamic slicing come at a cost in terms of service degradation (i.e., when not all the resources required by a VN can be provided), but the paper shows that the service degradation level introduced by the proposed solutions is very small.

Place, publisher, year, edition, pages
Optical Society of America, 2018. Vol. 10, no 1, p. A77-A90
Keywords [en]
5G transport, Dynamic slicing, IP over WDM, Multi-tenant networks, Network virtualization, Software defined networking
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-223287DOI: 10.1364/JOCN.10.000A77ISI: 000424046200011Scopus ID: 2-s2.0-85042273286OAI: oai:DiVA.org:kth-223287DiVA, id: diva2:1183712
Conference
Optical Fiber Communications Conference and Exhibition (OFC), Mar 19-23, 2017, Los Angeles, CA
Funder
EU, Horizon 2020, 671636VINNOVA, Kista 5G Transport Lab (K5) project
Note

QC 20180219

Available from: 2018-02-19 Created: 2018-02-19 Last updated: 2018-11-23Bibliographically approved
In thesis
1. Orchestration Strategies for Slicing in 5G Networks: Design and Performance Evaluation
Open this publication in new window or tab >>Orchestration Strategies for Slicing in 5G Networks: Design and Performance Evaluation
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The advent of 5th generation of mobile networks (5G) will introduce new challenges for the infrastructure providers (InPs). One of the major challenges is to provide a common platform for supporting a large variety of services. Such a platform can be realized by creating slices, which can be dynamically scaled up/down according to variation of service requirements. An InP generates revenue by accepting a slice request, however it has to pay a penalty if a slice cannot be scaled up when required. Hence, an InP needs to design intelligent policies (e.g., using big data analytics (BDA) or reinforcement learning (RL)) which maximize its net profit.

This thesis presents the design and performance evaluation of different orchestration strategies for dynamic slicing of infrastructure resources. Apart from simulation, some strategies are also experimentally demonstrated. The analysis is presented for both single-tenant and multi-tenant cases.

For single-tenant case, this thesis proposes a dynamic slicing strategy for a centralized radio access network with optical transport. Results show that an InP needs to deploy 31.4% less transport resources when using dynamic slicing as compared to overprovisioning.  For multi-tenant case, this thesis presents MILP formulations and heuristic algorithms for dynamic slicing. Results show that, via dynamic slicing, it is possible to achieve 5 times lower slice rejection probability as compared to static slicing.

The analysis is then extended to how BDA can be used in the slice admission and scaling processes. The proposed BDA-based admission policy increases the profit of an InP by up to 49% as compared to an admission policy without BDA. Moreover, the proposed BDA-based scaling policy lowers the penalty by more than 51% as compared to a first-come-first-served policy. Finally, this thesis presents how RL can be used for slice admission. The proposed policy performs up to 54.5% better as compared to deterministic heuristics.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2018. p. iii-xvii, 85
Series
TRITA-EECS-AVL ; 2018:56
Keywords
software defined networking, network function virtualization, orchestration, dynamic slicing, 5G, big data analytics, reinforcement learning
National Category
Communication Systems
Research subject
Information and Communication Technology
Identifiers
urn:nbn:se:kth:diva-235262 (URN)978-91-7729-912-7 (ISBN)
Public defence
2018-10-18, Ka-Sal C (Sal Sven-Olof Öhrvik), Electrum, Kungl Tekniska högskolan, Kistagången 16, Kista, 10:00 (English)
Opponent
Supervisors
Note

QC 20180919

Available from: 2018-09-19 Created: 2018-09-19 Last updated: 2018-09-20Bibliographically approved

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Raza, Muhammad RehanMonti, Paolo

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