RAN Runtime Slicing System for Flexible and Dynamic Service Execution Environment

Chang, Chia‐Yu; Nikaein, Navid

doi:10.1109/access.2018.2847610

Cited by 52 publications

(30 citation statements)

References 47 publications

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“…Authors in [10] layout the roadmap for a multi-tenant and multi-service architecture in the future evolution of mobile networks. Such architectures should enable flexible end-toend slicing via softwarization, virtualization, and disaggregation [11].…”

Section: Related Workmentioning

confidence: 99%

“…However, RAN slicing deals with the efficient sharing of the radio resources, i.e., time, frequency and space, among slices. Differently from the CN slicing, the unpredictability and variability of the wireless medium makes the RAN slicing a more challenging topic [11]. In particular, Radio Resource Management (RRM) is a crucial mechanism for ensuring the simultaneous fulfillment of the demands of the different slices.…”

Section: Related Workmentioning

confidence: 99%

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Framework for Slice-Aware Radio Resource Management Utilizing Artificial Neural Networks

et al. 2020

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For accommodating the heterogeneous services that are anticipated for the fifth-generation (5G) mobile networks, the concept of network slicing serves as a key technology. Spanning both the core network (CN) and radio access network (RAN), slices are end-to-end virtual networks that share the resources of a physical network. Slicing the RAN can be more challenging than slicing the CN since RAN slicing deals with the distribution of radio resources, which have fluctuating capacity and are harder to extend. Improving multiplexing gains, while assuring the slice isolation is the main challenging task for RAN slicing. This paper provides a flexible and configurable framework for RAN slicing, where diverse requirements of slices are simultaneously taken into account, and slice management algorithms adjust the control parameters of different radio resource management (RRM) mechanisms to satisfy the slices' service level agreements (SLAs). One of the proposed algorithms is based merely on heuristics and the other one utilizes an artificial neural network (ANN) to predict the behavior of the cellular network and make better decisions in the adjustment of the RRM mechanisms. Furthermore, a protection mechanism is devised to prevent the slices from negatively influencing each other's performances. A simulation-based analysis demonstrates that in presence of local or global overload of one of the slices, the ANN-based method increases the number of key performance indicators (KPIs) that fulfill their defined SLA targets. Finally, we show that the proposed protection mechanism can force the negative effects of an overloading slice to be contained to that slice and the other slices are not affected as severely.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Framework for Slice-Aware Radio Resource Management Utilizing Artificial Neural Networks

et al. 2020

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“…This calls for a unified and flexible execution environment to run multiple virtualised RAN and CN instances with the required levels of customisation over heterogeneous deployments. To this end, we present below the proposed runtime slicing system [11].…”

Section: Key Technical Enablers and Innovationsmentioning

confidence: 99%

Enable Advanced QoS-Aware Network Slicing in 5G Networks for Slice-Based Media Use Cases

Wang

Calero

Ricart‐Sanchez

et al. 2019

IEEE Trans. on Broadcast.

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Media use cases for emergency services require mission-critical levels of reliability for the delivery of media-rich services such as video streaming. With the upcoming deployment of the Fifth Generation (5G) networks, a wide variety of applications and services with heterogeneous performance requirements are expected to be supported, and any migration of missioncritical services to 5G networks presents significant challenges in the Quality of Service (QoS), for emergency service operators. This paper presents a novel SliceNet framework, based on advanced and customisable network slicing to address some of the highlighted challenges in migrating eHealth telemedicine services to 5G networks. An overview of the framework outlines the technical approaches in beyond the-state-of-the-art network slicing. Subsequently, the paper emphasises the design and prototyping of a media-centric eHealth use case, focusing on a set of innovative enablers towards achieving end-to-end QoS-aware network slicing capabilities, required by this demanding use case. Experimental results empirically validate the prototyped enablers and demonstrate the applicability of the proposed framework in such media-rich use cases.

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“…us, 5Gtango proposes the creation of a platform with validation and verication mechanisms for VNFs and Network Services, which is vendor-independent and owns an orchestrator compatible with existing Virtual Infrastructure Managers (VIMs) and SDN controllers [26]. e SLICENET project [4] focuses on the deployment of real end-to-end slicing in virtualised multidomain, multitenant 5G networks. e project targets three main use cases: the smart grid oriented to the energy vertical, the eHealth with connected ambulances, and the smart city use case.…”

Section: Mobile Information Systemsmentioning

confidence: 99%

“…SDR allows recreating base stations and other radio elements of the network with commercial off-the-shelf (COTS) components placed inside a computer. In addition, several open-source projects [4,5] were created to provide the elements of the core network by implementing the published standards directly in software. Nevertheless, SDR technology is not able to achieve the radio performance of the real equipment, and the different software solutions are still unstable or do not provide all the characteristic of the commercial ones.…”

Section: Introductionmentioning

confidence: 99%

Expanding GÉANT Testbeds Service to Support Pan-European 5G Network Slices for Research in the EuWireless Project

Rios

Valera-Muros

Gómez

et al. 2019

Mobile Information Systems

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This paper presents the design options for creating a Pan-European mobile network for research in the context of the European Horizon 2020 EuWireless project. The most likely direction is a platform that makes it easier to create network slices for research. In this context, we identify one promising technology to implement network slicing in 5G networks: the framework GÉANT Testbeds Service (GTS). GTS is currently a production service by GÉANT that offers remote construction and use of virtual testbeds for wired networks mapped to the real GÉANT infrastructure. These GTS-virtualized testbed environments conform to Software Define Networks (SDNs) principles and offer compute, storage, and switching resources, at scale and with line rate performance. In this paper, we explain how the current (wired oriented) GTS can be extended with the 5G components, such as radio access nodes (gNBs), transport networks, user devices, etc., in order to implement 5G network slices. Our first conclusion is that using GTS for EuWireless implementation is feasible, dramatically increasing the potential impact of this service in the research community.

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RAN Runtime Slicing System for Flexible and Dynamic Service Execution Environment

Cited by 52 publications

References 47 publications

Framework for Slice-Aware Radio Resource Management Utilizing Artificial Neural Networks

Framework for Slice-Aware Radio Resource Management Utilizing Artificial Neural Networks

Enable Advanced QoS-Aware Network Slicing in 5G Networks for Slice-Based Media Use Cases

Expanding GÉANT Testbeds Service to Support Pan-European 5G Network Slices for Research in the EuWireless Project

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