Data Plane and Control Architectures for 5G Transport Networks

The orchestration of radio, transport, and cloud resources is a key enabler for efficient service delivery in 5G networks. Orchestration can be achieved with a hierarchical software-defined networking (SDN) control architecture in which a global orchestrator operates above the domain controllers. In such an architecture, the abstraction of resources between the controllers and the orchestrator plays a fundamental role for the system performance. In order to reduce the orchestrator complexity, the controllers should hide as much detail as possible from the orchestrator. On the other hand, the more details are available to the orchestrator the more optimal resource orchestration strategy can be obtained. In order to assess this trade-off, we recently proposed two transport abstraction models, namely big switch (BiS) and virtual link (VL), for centralized radio access networks (C-RANs) with orchestration of radio and transport resources. We observed that VL can provide a more efficient resource orchestration than BiS at the expense of an increased implementation complexity. The contribution of this paper is twofold. We extend the BiS and VL models to make them applicable to any orchestration scenario. Then, we propose a new transport abstraction model, referred to as optical transport transformation (OTT), that aims at achieving efficient resource orchestration with a reduced implementation complexity. We compare the performance of these new abstraction models in a C-RAN use case in which backhaul and fronthaul traffic are carried over a dense wavelength division multiplexing (DWDM) network. Our results prove that in a C-RAN the best choice for the transport abstraction model depends on the availability and the reachability of the radio resources. If radio resources are scarce compared to transport resources, complex transport abstraction models are not needed and a BiS abstraction is the best choice. On the other hand, if radio resources are widely available and reachable, an OTT model guarantees the best overall performance.

QC 20160829

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“…1 the reference 5G network architecture is presented [14]. It is divided in data plane and control plane.…”

Section: Abstraction Modelsmentioning

confidence: 99%

“…Another example is the dynamic delivery of mobile access services, which involves the joint allocation of radio (e.g., baseband processing), transport (e.g., backhaul), and cloud (e.g., evolved packet core) resources [4], [5], [6].…”

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confidence: 99%

Abstraction Models for Optical 5G Transport Networks

Fiorani

Rostami

Wosinska

et al. 2016

J. Opt. Commun. Netw.

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QC 20160829

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“…T he fifth generation of mobile networks (5G) will see early deployments as soon as 2017 and will be introduced on a wider scale around 2020 with the objective of providing a high data rate and nearly ubiquitous connectivity to humans and machines [1]. This new paradigm will be possible thanks to the introduction of new radio access technologies as well as to the adoption of new radio network architectures [2].…”

Section: Introductionmentioning

confidence: 99%

“…Another example of network architecture is the centralized radio access network (C-RAN), which centralizes the baseband processing functions of several radio cells to achieve better radio coordination and lower cost [4]. These changes in the radio access segment will require significant modifications in the transport network, i.e., the segment in charge of connecting the radio base stations (RBSs) with the evolved packet core (EPC) [1,5]. For example, the continuous radio densification with SCs will translate into a high number of RBSs to be connected to the transport infrastructure.…”

Section: Introductionmentioning

confidence: 99%

“…For example, the continuous radio densification with SCs will translate into a high number of RBSs to be connected to the transport infrastructure. Another example is the Common Public Radio Interface (CPRI) protocol, used in C-RAN to connect the RBSs to the centralized baseband resources, which puts high-capacity requirements on the transport networks [1]. Overall, the future 5G transport networks will need to be highly scalable to efficiently support both an increasing number of RBSs and a higher capacity per RBS.…”

Section: Introductionmentioning

confidence: 99%

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Demonstration of Dynamic Resource Sharing Benefits in an Optical C-RAN

Raza

Fiorani

Rostami

et al. 2016

J. Opt. Commun. Netw.

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This is the published version of a paper published in .Citation for the original published paper (version of record):Raza, M R., Fiorani, M., Monti, P., Wosinska, L. Abstract-The next generation of mobile communication (i.e., 5G) will bring new challenges for the transport infrastructure, e.g., in terms of flexibility and capacity. The joint orchestration of radio and transport resources can help to address some of these challenges. One example is the possibility of reconfiguring the use of the transport network resources according to the spatial and temporal variations of the wireless traffic patterns. Using the concept of dynamic resource sharing, a limited pool of transport resources can be shared among a large number of radio base stations (RBSs), thus reducing considerably the overall deployment cost of the transport infrastructure. This paper proposes a provisioning strategy for a centralized radio access network with an optical transport whose wavelength resources can be dynamically shared among multiple RBSs. The proposed strategy utilizes a hierarchical software-defined networking control plane where a global orchestrator optimizes the usage of radio and transport resources. The benefits of the proposed strategy are assessed both by simulation and by experiment via an optical data plane emulator developed for this purpose. It is shown that the dynamic resource sharing can save up to 31.4% of transport resources compared to a conventional dimensioning approach, i.e., based on the overprovisioning of wavelength resources.

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A UAV Based Multi-object Detection Scheme to Enhance Road Condition Monitoring and Control for Future Smart Transportation

Yang

Zhang

et al. 2019

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Data Plane and Control Architectures for 5G Transport Networks

Cited by 67 publications

References 7 publications

Abstraction Models for Optical 5G Transport Networks

Abstraction Models for Optical 5G Transport Networks

Demonstration of Dynamic Resource Sharing Benefits in an Optical C-RAN

A UAV Based Multi-object Detection Scheme to Enhance Road Condition Monitoring and Control for Future Smart Transportation

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