Toward hardware‐accelerated QoS‐aware 5G network slicing based on data plane programmability

Ricart‐Sanchez, Ruben; Malagón, Pedro; Matencio‐Escolar, Antonio; Calero, José M. Alcaraz; Wang, Qi

doi:10.1002/ett.3726

Cited by 20 publications

(26 citation statements)

References 20 publications

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“…Baldini et al [31] described how the control plane of SliceNet is involved in meeting the E2E needs of different 5G verticals. Ricart-Sanchz et al [32] proposed a QoS-aware NS framework based on hardware acceleration to support data plane programmability [32]. Another important issue is resource deployment, and management policy for E2E NS [33,34].…”

Section: Qos Support For Reliable Nsmentioning

confidence: 99%

Resource Allocation Modeling for Fine-Granular Network Slicing in Beyond 5G Systems

Shu

Taleb

Song

2022

IEICE Trans. Commun.

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Through the concept of network slicing, a single physical network infrastructure can be split into multiple logically-independent Network Slices (NS), each of which is customized for the needs of its respective individual user or industrial vertical. In the beyond 5G (B5G) system, this customization can be done for many targeted services, including, but not limited to, 5G use cases and beyond 5G. The network slices should be optimized and customized to stitch a suitable environment for targeted industrial services and verticals. This paper proposes a novel Quality of Service (QoS) framework that optimizes and customizes the network slices to ensure the service level agreement (SLA) in terms of end-to-end reliability, delay, and bandwidth communication. The proposed framework makes use of network softwarization technologies, including software-defined networking (SDN) and network function virtualization (NFV), to preserve the SLA and ensure elasticity in managing the NS. This paper also mathematically models the end-to-end network by considering three parts: radio access network (RAN), transport network (TN), and core network (CN). The network is modeled in an abstract manner based on these three parts. Finally, we develop a prototype system to implement these algorithms using the open network operating system (ONOS) as a SDN controller. Simulations are conducted using the Mininet simulator. The results show that our QoS framework and the proposed resource allocation algorithms can effectively schedule network resources for various NS types and provide reliable E2E QoS services to end-users.

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Section: Qos Support For Reliable Nsmentioning

confidence: 99%

Resource Allocation Modeling for Fine-Granular Network Slicing in Beyond 5G Systems

Shu

Taleb

Song

2022

IEICE Trans. Commun.

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“…5G network slicing (NS) is considered an important innovation in mobile communications because of its ability to maximize sharing of network resources, flexibility optimization to accommodate various requirements from different vertical businesses [83]. NS also upgrades the capabilities of operation in terms of QoS and QoE [84]. NS intends to change the usual mobile network from an inert "one size fits all" concept to a dynamic concept with logical partitions and logical networks, having suitable isolation, resources as well as topology optimized for a specific function or service such as UCs, traffic category or individual [85].…”

Section: G Network Slicingmentioning

confidence: 99%

5G Mobile Communication Applications: A Survey and Comparison of Use Cases

et al. 2021

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The mobile demands and future business context are anticipated to be resolved by the fifthgeneration (5G) of mobile communication systems. It is expected to provide an utterly mobile device, connected society, and support the demanding services of various use cases (UCs). This is intended to meet the demand requirement by providing services at tens of Gbps in terms of data rates, higher mobility range, lower latencies, and massive connectivity density devices per square kilometer. A comprehensive and up-todate survey of the different developed and proposed use cases is presented in this paper. The first part of the paper presents the overview of the new 5G Architecture by introducing new features such as the new radio interface (New Radio), an overview of the 5G Core Network, minimum requirements, and the Radio Access Network, 5G spectrum requirements and other fundamentals of the network. Secondly, a detailed review of the developed and proposed use cases for 5G communications by the standards development organizations (SDO) and other key players in mobile communication is provided. Thirdly, we went ahead to propose spectrum bands for the deployment of the various use cases based on the low-, mid-, and high-band spectrum and further classified the use cases with respect to their relevance and family, identifying the IMT-2020 test environments and the usage scenarios derived by the 3GPP, fourthly, the channel capacity and the bandwidth of the spectrum was studied, simulated and compared to ascertain the spectrum proposed in this paper for each UC family. Hence, this paper serves as a guideline for understanding the usage scenarios for the future 5G deployment in various environments. This would allow system developers to design and implement 5G channel characterization models specific to the usage scenarios to meet the system requirements.

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“…In case the reader is more interested in understanding the delays of the UWS-FPGA Slicing Core implemented, our previous work Ricart-Sanchez et al [2] provides an in-depth explanation. This contribution is focused on the application to such previous results into the smart grid use case, including the support of the R-GOOSE protocol.…”

Section: Deparsermentioning

confidence: 99%

“…The most known and cited definition of a 5G slice, is presented by the NGMN, which describes a 5G slice as a collection of 5G network functions and specific Radio Access Technology (RAT) settings that are combined together for the specific use case or business model, supporting the communication service of particular connection type with a specific way of handling the control and user plane for this service. Taking into consideration all the definitions proposed by the different organizations and industry alliances, this paper follows the approach presented in [2], that describes a 5G slice as the isolation of performance of a set of network flows, allowing the deployment of multiple logical networks on the top of a common shared physical device.…”

Section: Introductionmentioning

confidence: 99%

Hardware-Based Network Slicing for Supporting Smart Grids Self-Healing over 5G Networks

Ricart‐Sanchez

Aleixo

Wang

et al. 2020

2020 IEEE International Conference on Communications Workshops (ICC Workshops)

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As a fundamental technology in the Fifth-Generation (5G) mobile networks, network slicing creates multiple logical networks for various vertical businesses over the same physical 5G infrastructure to achieve cost-effective service provisioning. Meanwhile, mission-critical vertical businesses would require a very high level of guaranteed Quality of Service (QoS) that is beyond software-based network slicing approaches. In this paper, we address a highly demanding Smart Grid Self-Healing Automatic Reconfiguration use case to ensure ultra-Reliable and Low-Latency communications (uRLLC) through improved network slicing based on programmable hardware acceleration. Empirical results have demonstrated the superior performance of the proposed approach in meeting the strict and challenging QoS requirements of this use case.

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Toward hardware‐accelerated QoS‐aware 5G network slicing based on data plane programmability

Abstract: Toward hardwareaccelerated QoS-aware 5G network slicing based on data plane programmability. Transactions on Emerging Telecommunications Technologies.

Cited by 20 publications

References 20 publications

Resource Allocation Modeling for Fine-Granular Network Slicing in Beyond 5G Systems

Resource Allocation Modeling for Fine-Granular Network Slicing in Beyond 5G Systems

5G Mobile Communication Applications: A Survey and Comparison of Use Cases

Hardware-Based Network Slicing for Supporting Smart Grids Self-Healing over 5G Networks

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