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Demonstration of Dynamic Resource Sharing Benefits in an Optical CRAN
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Optical Network Laboratory (ON Lab). Kungliga Tekniska högskolan.ORCID iD: 0000-0002-8026-7682
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Optical Network Laboratory (ON Lab).ORCID iD: 0000-0002-5636-9910
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Optical Network Laboratory (ON Lab).ORCID iD: 0000-0001-6704-6554
2016 (English)In: Journal of Optical Communications and Networking, ISSN 1943-0620, E-ISSN 1943-0639, Vol. 8, no 8, p. 621-632Article in journal (Other academic) Epub ahead of print
Abstract [en]

The next generation of mobilecommunication (i.e., 5G) will bring new challengesfor the transport infrastructure, e.g. in terms offlexibility and capacity. The joint orchestration ofradio and transport resources can help to addresssome of these challenges. One example is thepossibility to reconfigure the use of the transportnetwork resources according to the spatial andtemporal variations of the wireless traffic patterns.Using the concept of dynamic resource sharing, alimited pool of transport resources can be sharedamong a large number of radio base stations (RBSs)thus reducing considerably the overall deploymentcost of the transport infrastructure.This paper proposes a provisioning strategy for acentralized radio access network (C-RAN) with anoptical transport whose wavelength resources can bedynamically shared among multiple RBSs. Theproposed strategy utilizes a hierarchical softwaredefined networking (SDN) control plane where aglobal orchestrator optimizes the usage of radio andtransport resources. The benefits of the proposedstrategy are assessed both by simulation and byexperiment via an optical data plane emulatordeveloped for this purpose. It is shown that thedynamic resource sharing can save up to 31.4% oftransport resources compared to a conventionaldimensioning approach, i.e., based onoverprovisioning of wavelength resources.

Place, publisher, year, edition, pages
IEEE Press, 2016. Vol. 8, no 8, p. 621-632
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-192994DOI: 10.1364/JOCN.8.000621ISI: 000383862500009Scopus ID: 2-s2.0-84980332083OAI: oai:DiVA.org:kth-192994DiVA, id: diva2:974089
Note

QC 20160923

Available from: 2016-09-23 Created: 2016-09-23 Last updated: 2018-09-19Bibliographically approved
In thesis
1. Flexible and Programmable 5G Transport Networks
Open this publication in new window or tab >>Flexible and Programmable 5G Transport Networks
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The advent of 5th generation of mobile networks (5G) will introduce some new challenges for the transport network. Different strategies can be employed by the network providers to address these challenges with the aim to achieve an efficient utilization of network resources. The most feasible option to achieve this goal is to introduce intelligence in the transport infrastructure by designing a flexible and programmable transport network.

Network function virtualization (NFV) and dynamic resource sharing (DRS) are two possible techniques for realizing a flexible transport network. NFV allows to dynamically push network functions to different locations in the network, while DRS allows for sharing transport resources in a flexible manner. Both of these strategies can be realized by employing a programmable control framework based on software defined networking (SDN), which has implications on both the network data and control planes. However, this thesis specifically focuses on the data plane aspects of NFV and the control plane aspects of DRS.

Considering the network caching as a specific example of network function, the data plane aspects of NFV are studied in terms of different architectural options for cache placement in order to see which options are the most efficient in terms of network power consumption and cost. The results presented in this thesis show that placing large-sized caches farther in the network for a large group of users is the most efficient approach.

The control plane aspects of DRS are analyzed in terms of which provisioning strategy should be used for sharing a limited amount of transport resources. The analysis is presented for both a single-tenant case (i.e., where the role of service and network provider is played by the same entity), and a multi-tenant case (i.e., where a network provider manages the resources assigned to different service providers in an intelligent way). The results show that DRS performs much better than the conventional static approach (i.e., without sharing of resources), which translates into significant cost savings for the network providers.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2016. p. 43
Series
TRITA-ICT ; 2016:39
Keywords
5G transport, network function virtualization, dynamic resource sharing, software-defined networking, centralized RAN, network virtualization.
National Category
Communication Systems
Research subject
Information and Communication Technology
Identifiers
urn:nbn:se:kth:diva-196525 (URN)978-91-7729-186-2 (ISBN)
Presentation
2016-12-19, Ka-Sal C (Sal Sven-Olof Öhrvik), Electrum, Kungl Tekniska högskolan, Kistagången 16, Kista, 10:00 (English)
Opponent
Supervisors
Note

QC 20161115

Available from: 2016-11-15 Created: 2016-11-15 Last updated: 2016-11-16Bibliographically approved
2. 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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