Network Slicing: an Overview

Napolitano, Annalisa; Giorgetti, A.; Kondepu, Koteswararao; Valcarenghi, L.; Castoldi, P.

doi:10.1109/rtsi.2018.8548449

Cited by 9 publications

(4 citation statements)

References 3 publications

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“…The NGMN network alliance provides a network slicing conceptual architecture outline with three layers. It defines an end-user service or a business Service Instance Layer (SIL), a Network Slice Instance (NSI) providing a set of network functions required by a service instance, and a resource layer [26].…”

Section: A Network Slicing Standardization Initiativesmentioning

confidence: 99%

Enhancing Network Slicing Architectures With Machine Learning, Security, Sustainability and Experimental Networks Integration

Martins

Carvalho²,

Moreira³

et al. 2023

IEEE Access

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Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP's proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for endto-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.

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Section: A Network Slicing Standardization Initiativesmentioning

confidence: 99%

Enhancing Network Slicing Architectures With Machine Learning, Security, Sustainability and Experimental Networks Integration

Martins

Carvalho²,

Moreira³

et al. 2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…O fatiamento da rede na tecnologia 5G permite a criação de redes virtualizadas independentes para atender os diferentes serviços ou casos de uso [13], [19]. As redes virtuais independentes são denominadas instâncias de fatias de rede, ou NSIs.…”

Section: Cenários De Uso De Redes 5g Fatiamento De Redes E Nstsunclassified

“…Uma forma de satisfazer as diferentes demandas dos usuários de diferentes cenários e aplicações é segmentá-los em grupos e definir fatias lógicas dedicadas da rede para cada grupo. Este conceito, conhecido como Network Slicing (NS) [8], [16], [19], confere flexibilidade e programabilidade dos recursos de rede. Este artigo propõe modelos de fatias de redes, os Network Slice Templates (NSTs), que são usados na criação de instâncias de fatias de rede (Network Slice Instances -NSIs).…”

Section: Introductionunclassified

Modelos para Fatiamento de Redes 5G

Fagundes,

Lovisolo,

Rubinstein

2023

Anais Do XLI Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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Resumo-Este artigo propõe modelos de fatias de rede (NSTs -Network Slice Templates) para redes 5G para diferentes cenários de uso da rede definidos pelo IMT-2020: eMBB (enhanced Mobile BroadBand), URLLC (Ultra Reliable Low Latency Communications) e mMTC (massive Machine-Type Communications). Simulase uma rede 5G sob o modelo NST proposto para o cenário eMBB Urbano Macro a fim de analisar se o NST proposta atende ao SLA (Service Level Agreements) definidos para esse perfil de uso.

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“…5G networks aim to support lots of applications that are characterized by diverse performance requirements. Network slicing [1] is the key technology enabler to achieve this target. Much research has been done on how to create network services using network slicing [2] [3].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Dedicated Slices of Different Configurations in 5G Core

Lin¹,

Chai²

2021

JCC

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Network slicing is one of the most important concepts in 5G networks. It is enabled by the Network Function Virtualization (NFV) technology to allow a set of Virtual Network Functions (VNFs) to be interconnected to form a Network Service (NS). When network slices are created in 5G, some are shared among different 5G services while the others are dedicated to specific 5G services. The latter are called dedicated slices. Dedicated slices can be constructed with different configurations. In this research, dedicated slices of different configurations in 5G Core were evaluated in order to discover which one would perform better than the others. The performance of three systems would be compared: 1) Free5GC Stage 2 with each dedicated slice consisting of only UPF; 2) Free5GC Stage 3 with each dedicated slice consisting of only UPF; 3) Free5GC Stage 3 with each dedicated slice consisting of both SMF and UPF in terms of their registration time, response time, throughput, resource cost, and CPU utilization. It is shown that not one of the above systems will always be the best choice; based on the requirements, a specific system may be the best under a specific situation.

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Network Slicing: an Overview

Cited by 9 publications

References 3 publications

Enhancing Network Slicing Architectures With Machine Learning, Security, Sustainability and Experimental Networks Integration

Enhancing Network Slicing Architectures With Machine Learning, Security, Sustainability and Experimental Networks Integration

Modelos para Fatiamento de Redes 5G

Evaluating Dedicated Slices of Different Configurations in 5G Core

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