Towards a unified fronthaul-backhaul data plane for 5G The 5G-Crosshaul project approach

Cavaliere, Fabio; Iovanna, Paola; Mangues‐Bafalluy, Josep; Baranda, Jorge; Nunez-Martinez, Jose; Lin, Kun‐Yi Andrew; Chang, Hsien Wen; Chanclou, Philippe; Farkas, Peter; Gomes, Jesse; Cominardi, Luca; Mourad, Alain; Oliva, Antonio de la; Hernández, José Alberto; Larrabeiti, David; Giglio, Andrea Di; Paolicelli, Antonia; Ödling, Per

doi:10.1016/j.csi.2016.11.005

Cited by 18 publications

(12 citation statements)

References 6 publications

(3 reference statements)

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“…fronthaul transport network where reconfiguration of network elements is done in a multi-tenant environment [196,202] . The 5G-Crosshaul architecture implementation consists of: (i) a control plane that provides an abstraction of a network model and integrates the Xhaul Control Infrastructure (XCI); (ii) a unified data plane to provide novel Xhaul Packet Forwarding Element (XFE).…”

Section: G-crosshaulmentioning

confidence: 99%

5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges

et al. 2020

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a b s t r a c tThe increasing consumption of multimedia services and the demand of high-quality services from customers has triggered a fundamental change in how we administer networks in terms of abstraction, separation, and mapping of forwarding, control and management aspects of services. The industry and the academia are embracing 5G as the future network capable to support next generation vertical applications with different service requirements. To realize this vision in 5G network, the physical network has to be sliced into multiple isolated logical networks of varying sizes and structures which are dedicated to different types of services based on their requirements with different characteristics and requirements (e.g., a slice for massive IoT devices, smartphones or autonomous cars, etc.). Softwarization using Software-Defined Networking (SDN) and Network Function Virtualization (NFV)in 5G networks are expected to fill the void of programmable control and management of network resources.In this paper, we provide a comprehensive review and updated solutions related to 5G network slicing using SDN and NFV. Firstly, we present 5G service quality and business requirements followed by a description of 5G network softwarization and slicing paradigms including essential concepts, history and different use cases. Secondly, we provide a tutorial of 5G network slicing technology enablers including SDN, NFV, MEC, cloud/Fog computing, network hypervisors, virtual machines & containers. Thidly, we comprehensively survey different industrial initiatives and projects that are pushing forward the adoption of SDN and NFV in accelerating 5G network slicing. A comparison of various 5G architectural approaches in terms of practical implementations, technology adoptions and deployment strategies is presented. Moreover, we provide a discussion on various open source orchestrators and proof of concepts representing industrial contribution. The work also investigates the standardization efforts in 5G networks regarding network slicing and softwarization. Additionally, the article presents the management and orchestration of network slices in a single domain followed by a comprehensive survey of management and orchestration approaches in 5G network slicing across multiple domains while supporting multiple tenants. Furthermore, we highlight the future challenges and research directions regarding network softwarization and slicing using SDN and NFV in 5G networks.Crown (A .A . Barakabitze). tems [1,2,3] . The increasing number of smart devices (e.g., tablets and smartphones) and the growing number of bandwidth-hungry mobile applications (e.g., live video streaming, online video gaming) which demand higher spectral efficiency than that of 4G systems are posing significant challenges in 5G. The Cisco Visual Networking Index (VNI) Forecast [4] predicts that IP video traffic will be 82% of all consumer Internet traffic by 2022, up from 75% in 2017. Mobile video traffic alone will account for 78% of the global mobile data traffic. W...

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Section: G-crosshaulmentioning

confidence: 99%

5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges

et al. 2020

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“…An extensive set of studies have developed SDN-based architectures for the backhaul of wireless network traffic [16][17][18]. Given the complexity of the backhaul, most of this work has considered layered or tiered architectures [12,[19][20][21][22][23][24], whereby intermediate gateway nodes perform various protocol related functions [25][26][27][28]. For instance, there may be gateway nodes that interface with Internet of Things nodes [29,30] or specific wireless network technologies, such as wireless local area networks [31].…”

Section: Sdn-based Backhaul Architecturesmentioning

confidence: 99%

“…where τ S O , τ O G , and τ G N , are, respectively, the RTTs between the SDN orchestrator and the operators, between the operators and the GWs, as well as between the eNBs and the GWs (see also Figure 2, where τ G N has been normalized to one). The inequalities in (18)- (19) indicate that if we want to act fast, e.g., reduce P and L (possibly to the minimum refresh times) we need to perform fewer iterations. Vice versa, if we want to perform more iterations, we must be willing to act slower in updating the decisions x and y.…”

Section: Stochastic Optimization and Temporal Decompositionmentioning

confidence: 99%

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A Multi-Layer Multi-Timescale Network Utility Maximization Framework for the SDN-Based LayBack Architecture Enabling Wireless Backhaul Resource Sharing

et al. 2019

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With the emergence of small cell networks and fifth-generation (5G) wireless networks, the backhaul becomes increasingly complex. This study addresses the problem of how a central SDN orchestrator can flexibly share the total backhaul capacity of the various wireless operators among their gateways and radio nodes (e.g., LTE enhanced Node Bs or Wi-Fi access points). In order to address this backhaul resource allocation problem, we introduce a novel backhaul optimization methodology in the context of the recently proposed LayBack SDN backhaul architecture. In particular, we explore the decomposition of the central optimization problem into a layered dual decomposition model that matches the architectural layers of the LayBack backhaul architecture. In order to promote scalability and responsiveness, we employ different timescales, i.e., fast timescales at the radio nodes and slower timescales in the higher LayBack layers that are closer to the central SDN orchestrator. We numerically evaluate the scalable layered optimization for a specific case of the LayBack backhaul architecture with four layers, namely a radio node (eNB) layer, a gateway layer, an operator layer, and central coordination in an SDN orchestrator layer. The coordinated sharing of the total backhaul capacity among multiple operators lowers the queue lengths compared to the conventional backhaul without sharing among operators.

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“…There are various research studies that provide the emergent portfolio of fronthaul or backhaul solutions including novel technologies and legacy methods such as [32] [33]. The core part of this survey study is summarizing the prior research study in the state-of-art-of evolution of 5G mobile network backhaul solutions.…”

Section: Literature Of 5g Backhaul Networkmentioning

confidence: 99%

A Comprehensive Research Study on 5G Backhauling: Solutions, Requirements and Challenges

Deepa¹

2019

CAE

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The 5 th generation cellular technology i.e. 5G network is considered as most emerging wireless technology to enable the IoTs. Nevertheless, the key challenge is to offer a ubiquitous and efficient backhaul networking to small cell devices. There are several backhaul solutions are available which can address the backhaul challenges for 5G networks. In this context, the present survey study providing a detail overview on 5G infrastructure with respect to different architectural concept followed by different backhaul solutions. A qualitative review on prior backhaul solutions and different standards are discussed. Furthermore, highlighting perceives solutions over 5G backhaul networks, which are not apparent when backhaul networking is examined as individual part of 5G technology. This comprehensive survey study is key in exploring the significant catalysts which are supposed to mutually cover the way to solve the new wireless backhaul challenge. In the last, have defined key points generated from existing solution and providing consolidated research directions for new 5G backhaul network deployment.

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Towards a unified fronthaul-backhaul data plane for 5G The 5G-Crosshaul project approach

Cited by 18 publications

References 6 publications

5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges

5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges

A Multi-Layer Multi-Timescale Network Utility Maximization Framework for the SDN-Based LayBack Architecture Enabling Wireless Backhaul Resource Sharing

A Comprehensive Research Study on 5G Backhauling: Solutions, Requirements and Challenges

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