Dynamic Virtual Resource Allocation for 5G and Beyond Network Slicing

Song, Fei; Li, Jun; Ma, Chuan; Zhang, Yijin; Shi, Long; Jayakody, Dushantha Nalin K.

doi:10.1109/ojvt.2020.2990072

Cited by 48 publications

(28 citation statements)

References 31 publications

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“…For this vision to be realistic, network operators should be able to orchestrate their capabilities across several points in the infrastructure dynamicallydynamic network slicing [78], [79]. Furthermore, to satisfy critical mMTC requirements, we need a different approach to resource allocation among network slices for guaranteed and context aware slicing of resources-constrained network slicing [80].…”

Section: A Dynamic and Constrained Network Slicingmentioning

confidence: 99%

Towards Enabling Critical mMTC: A Review of URLLC Within mMTC

et al. 2020

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Massive machine-type communication (mMTC) and ultrareliable and low-latency communication (URLLC) are two key service types in the fifth-generation (5G) communication systems, pursuing scalability and reliability with low-latency, respectively. These two extreme services are envisaged to agglomerate together into critical mMTC shortly with emerging use cases (e.g., wide-area disaster monitoring, wireless factory automation), creating new challenges to designing wireless systems beyond 5G. While conventional network slicing is effective in supporting a simple mixture of mMTC and URLLC, it is difficult to simultaneously guarantee the reliability, latency, and scalability requirements of critical mMTC (e.g., < 4ms latency, 106 devices/km 2 for factory automation) with limited radio resources. Furthermore, recently proposed solutions to scalable URLLC (e.g., machine learning aided URLLC for driverless vehicles) are ill-suited to critical mMTC whose machine type users have extremely limited energy budget and computing capability that should be tightly optimized for given tasks. In view of this, this paper aims to characterize promising use cases of critical mMTC and search for their possible solutions. To this end, we first review the state-of-theart (SOTA) technologies for separate mMTC and URLLC services and then identify key challenges from conflicting SOTA requirements, followed by potential approaches to prospective critical mMTC solutions at different layers. Index Terms-Ultra reliable low latency communication (URLLC), massive machine type communications (mMTC), critical mMTC, 5G, beyond 5G.

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Section: A Dynamic and Constrained Network Slicingmentioning

confidence: 99%

Towards Enabling Critical mMTC: A Review of URLLC Within mMTC

et al. 2020

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“…However, such IIoT use-cases have posed a significant challenge of diverse Quality-of-Services (QoS) requirements regarding data rate, latency and reliability, and priority, as shown in Table I. As a result, the network softwarization [1] is considered as potential trend that transforms the existing IIoT networks into the software-based network slicing solutions which can operate on the general-built physical network infrastructures [2]. Within the current virtual RAN (vRAN) and cloud RAN [6].…”

Section: Introductionmentioning

confidence: 99%

Elastic O-RAN Slicing for Industrial Monitoring and Control: A Distributed Matching Game and Deep Reinforcement Learning Approach

Abedin¹,

Mahmood²,

Tran³

et al. 2021

Preprint

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In this work, we design an elastic open radio access network (O-RAN) slicing for the industrial Internet of things (IIoT). Unlike IoT, IIoT poses additional challenges such as severe communication environment, network-slice resource demand variations, and on-time information update from the IIoT devices during industrial production. First, we formulate the O-RAN slicing problem for on-time industrial monitoring and control where the objective is to minimize the cost of fresh information updates (i.e., age of information (AoI)) from the IIoT devices (i.e., sensors) while maintaining the energy consumption of those devices with the energy constraint as well as O-RAN slice isolation constraints. Second, we propose the intelligent ORAN framework based on game theory and machine learning to mitigate the problem’s complexity. We propose a two-sided distributed matching game in the O-RAN control layer that captures the IIoT channel characteristics and the IIoT service priorities to create IIoT device and small cell base station (SBS) preference lists. We then employ an actor-critic model with a deep deterministic policy gradient (DDPG) in the O-RAN service management layer to solve the resource allocation problem for optimizing the network slice configuration policy under time varying slicing demand. While the matching game helps the actor-critic model, the DDPG enforces the long-term policy-based guidance for resource allocation that reflects the trends of all IIoT devices and SBSs satisfactions with the assignment. Finally, the simulation results show that the proposed solution enhances the performance gain for the IIoT services by serving an average of 50% and 43.64% more IIoT devices than the baseline approaches. <br>

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“…Por outro lado, a NFV é desenvolvida para resolver limitações da infraestrutura, como por exemplo, a escassez de equipamentos de comunicação de uma rede. O núcleo da NFV é constituído pela virtualização das funções de rede e funcionam em máquinas virtuais em servidores comuns sem a necessidade de um hardware dedicado [1].…”

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Escalonamento de recursos em redes móveis 5G utilizando Network Slicing para os serviços URLLC e eMBB

Lopes¹,

Silva²,

Rocha³

2021

Anais Do XXXIX Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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Resumo-Neste artigo, propõe-se uma solução para o problema de otimização utilizando escalonadores de recursos em redes móveis 5G. Estes escalonadores alocam largura de banda para os Equipamentos dos Usuários (UEs -User Equipments) dentro da área de cobertura de pequenas células -(Small Cells), considerando o paradigma de fatiamento de rede (NS -Network Slicing). A simulação é proposta para os UEs que utilizam os serviços de comunicações ultra confiáveis e de baixa latência (URLLC -Ultra-Reliable and Low-Latency Communications) e banda larga móvel melhorada (eMBB -Enhanced Mobile Broadband) com diferentes Esquemas de Modulação e Codificação (MCS -Modulation and Coding Schemes).

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Dynamic Virtual Resource Allocation for 5G and Beyond Network Slicing

Cited by 48 publications

References 31 publications

Towards Enabling Critical mMTC: A Review of URLLC Within mMTC

Towards Enabling Critical mMTC: A Review of URLLC Within mMTC

Elastic O-RAN Slicing for Industrial Monitoring and Control: A Distributed Matching Game and Deep Reinforcement Learning Approach

Escalonamento de recursos em redes móveis 5G utilizando Network Slicing para os serviços URLLC e eMBB

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