A Service‐Oriented Approach for Radio Resource Management in Virtual RANs

Rouzbehani, Behnam; Correia, Luıs M.; Caeiro, Luisa

doi:10.1155/2018/4163612

Cited by 6 publications

(3 citation statements)

References 36 publications

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“…Following [4], [5], we consider the downlink transmission of a 5G base station (BS) with a virtualized RAN and network slicing. We assume that there are 𝑆 instantiated slices at the BS and denote their set by S , |S | = 𝑆.…”

Section: System Model and Notationmentioning

confidence: 99%

A simulator for analyzing a network slicing policy with SLA-based performance isolation of slices

Polyakov

Yarkina

Samouylov

2021

Discrete and Continuous Models

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Efficient allocation of radio access network (RAN) resources remains an important challenge with the introduction of 5G networks. RAN virtualization and division into logical subnetworks - slices - puts this task into a new perspective. In the paper we present a software tool based on the OMNeT++ platform and developed for performance analysis of a network slicing policy with SLA-based slice performance isolation. The tool is designed using the object-oriented approach, which provides flexibility and extensibility of the simulation model. The paper briefly presents the slicing policy under study and focuses on the simulators architecture and design. Numerical results are provided for illustration.

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Section: System Model and Notationmentioning

confidence: 99%

A simulator for analyzing a network slicing policy with SLA-based performance isolation of slices

Polyakov

Yarkina

Samouylov

2021

Discrete and Continuous Models

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“…We consider the downlink transmission from a 4G/5G co-located base station (featuring both LTE and NR radio access technologies) at which radio access resource virtualization and network slicing are implemented [40]. Note that the proposed approach is applicable to a 5G-only network as well, however, although the network architecture for 5G has not yet been standardized (in contrast to its radio interface), the likely upcoming solution is a full integration with 4G (akin to 2G/GSM or 3G/UMTS).…”

Section: Basic Assumptionsmentioning

confidence: 99%

An Analytical Model for 5G Network Resource Sharing with Flexible SLA-Oriented Slice Isolation

et al. 2020

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Network slicing is a novel key technology in 5G networks which permits to provide a multitude of heterogeneous communication services over a common network infrastructure while satisfying strict Quality of Service (QoS) requirements. Since radio spectrum resources are inherently scarce, the slicing of the radio access network should rely on a flexible resource sharing policy that provides efficient resource usage, fairness and slice isolation. In this article, we propose such a policy for bandwidth-greedy communication services. The policy implies a convex programming problem and is formalized to allow for session-level stochastic modeling. We developed a multi-class service system with service rates obtained as a solution to the optimization problem, a Markovian Arrival Process and state-dependent preemptive priorities. We use matrix-analytic methods to find the steady state distribution of the resulting continuous-time Markov chain and the expressions for important performance metrics, such as data rates. Numerical analysis illustrates the efficiency of the proposed slicing scheme compared to the complete sharing and complete partitioning policies, showing that our approach leads to a data rate about the double of that obtained under complete partitioning for the analyzed scenario.

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“…The formerly proposed inter-slice Radio Resource Management (RRM) algorithms either allocate resources in passive mode (i.e. adopt the allocation after observation of demand change) [5] or they allocate based on maximum demand assumption [6,7]. Dynamic reservation of resources for the slices is also another approach to inter-slice radio resource management [8].…”

Section: Introductionmentioning

confidence: 99%

Elastic Slice-Aware Radio Resource Management with AI-Traffic Prediction

Khatibi

Jano

2019

2019 European Conference on Networks and Communications (EuCNC)

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Network virtualisation and network slicing are the two essential innovations in the next generation of mobile networks also known as the 5G networks. Based on these innovations, multiple network slices with different requirements and objectives can share the same physical infrastructure. The techniques to efficiently allocate the available radio resources to different slices based on their requirements and their priority, also known as inter-slice radio resource management, has been the subject of many studies. The formerly proposed algorithms either assume the slices request maximum contracted data rates or they react passively as the demands arrive. This paper proposes to use Artificial Intelligence (AI) approaches to learn the pattern of the traffic demand of each network slices and predict the demands in the next decision interval. Based on the prediction of the slices' demands, a novel model for elastic inter-slice radio resource management is proposed to increase the multiplexing gain while not compromising the quality of offered connectivity services to the slices. The proposed model is evaluated using a practical scenario. The numeric results show that while the performance of the model under full demand is similar to former models, its elastic resource management enables more efficient resource allocation when the traffic demands vary over time.

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A Service‐Oriented Approach for Radio Resource Management in Virtual RANs

Cited by 6 publications

References 36 publications

A simulator for analyzing a network slicing policy with SLA-based performance isolation of slices

A simulator for analyzing a network slicing policy with SLA-based performance isolation of slices

An Analytical Model for 5G Network Resource Sharing with Flexible SLA-Oriented Slice Isolation

Elastic Slice-Aware Radio Resource Management with AI-Traffic Prediction

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