Network slicing - enabled RAN management for 5G: Cross layer control based on SDN and SDR

Barmpounakis, Sokratis; Maroulis, Nikolaos; Papadakis, Michael; Tsiatsios, George; Soukaras, Dimitrios; Alonistioti, Nancy

doi:10.1016/j.comnet.2019.106987

Cited by 29 publications

(20 citation statements)

References 9 publications

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“…Network slicing for different smart services involves diverse communication networks and computing technologies at the infrastructure layer [48]. These technologies include edge computing technologies, cloud, IoT networks, telecommunication networks, and satellites.…”

Section: Physical Infrastructurementioning

confidence: 99%

Network Slicing: Recent Advances, Taxonomy, Requirements, and Open Research Challenges

et al. 2020

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Fifth-generation (5G) and beyond networks are envisioned to provide multi-services with diverse specifications. Network slicing is identified as a key enabling technology to enable 5G networks with multi-services. Network slicing allows a transition from a network-as-an-infrastructure setup to a networkas-a-service to enable numerous 5G smart services with diverse requirements. Although several surveys and tutorials have discussed network slicing in detail, there is no comprehensive study discussing the taxonomy and requirements of network slicing. In this paper, we present and investigate key recent advances of network slicing towards enabling several Internet of Things (IoT) smart applications. A taxonomy is devised for network slicing using different parameters: key design principles, enablers, slicing resources levels, service function chaining schemes, physical infrastructures, and security. Furthermore, we discuss key requirements for network slicing to enable smart services. Finally, we present several open research challenges along with possible guidelines for network slicing.

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Section: Physical Infrastructurementioning

confidence: 99%

Network Slicing: Recent Advances, Taxonomy, Requirements, and Open Research Challenges

et al. 2020

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“…These aforementioned problems are resolved in the proposed research using network slicing, resource allocation, dynamic offloading, security, and packet classification. 3 RA in an SDN/NFV-enabled 5G network was designed using the processing capabilities of mobile device authentication, traffic scheduling, network slicing, and resource allocation and dynamic offloading.…”

Section: Problem Definitionmentioning

confidence: 99%

“…HopFieldNet is designed with a single layer of input nodes that are connected to other nodes as feedback connections that assist in redirecting the output to the input. Here, the number of nodes, inputs, and outputs are equal and, in this T-S 3 RA system, the total number of resources nodes are built. The nodes are measured to be double-threshold nodes since they are served in a content-addressable memory system.…”

Section: Network Slicing and Resource Allocationmentioning

confidence: 99%

“…Network slicing is an important issue that needs to be addressed for 5G networks under a single physical infrastructure. In general, network slicing is defined as selecting appropriate slices and allocating resources as per the specific service type of a user [1][2][3][4]. Currently, network equipment requires high service satisfaction rates.…”

Section: Introductionmentioning

confidence: 99%

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T-S3RA: Traffic-Aware Scheduling for Secure Slicing and Resource Allocation in SDN/NFVEnabled 5G Networks

Ramadhan¹

2021

IJETT

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Network slicing and resource allocation play pivotal roles in software-defined network (SDN)/network function virtualization (NFV)-assisted 5G networks. In 5G communications, the traffic rate is high, necessitating high data rates and low latency. Deep learning is a potential solution for overcoming these constraints. Secure slicing avoids resource wastage; however, DDoS attackers can exploit the sliced network. Therefore, we focused on secure slicing with resource allocation under massive network traffic. Traffic-aware scheduling is proposed for secure slicing and resource allocation over SDN/NFV-enabled 5G networks. In this approach (T-S3RA), user devices are authenticated using Boolean logic with a password-based key derivation function. The traffic is scheduled in 5G access points, and secure network slicing and resource allocation are implemented using deep learning models such as SliceNet and HopFieldNet, respectively. To predict DDoS attackers, we computed the Renyi entropy for packet classification. Experiments were conducted using a network simulator with 250 nodes in the network topology. Performance was evaluated using metrics such as throughput, latency, packet transmission ratio, packet loss ratio, slice capacity, bandwidth consumption, and slice acceptance ratio. T-S3RA was implemented in three 5G use cases with different requirements, including massive machine-type communication, ultra-reliable low-latency communication, and enhanced mobile broadband.

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“…More recently the advances in hardware integration allow to have embedded SDR architectures based on System on Chip (SoC) combining software and hardware computational resources. This enlarges the scope of embedded SDR applications as now they are capable to capture modern wireless standards [4], exhibit cybersecurity vulnerabilities [5] or apply specific real-time processes to signals [6]. In any case, SDR has proved to be a precious tool for prototyping (due to its reasonable cost and simple configuration) and has also strong assets for pedagogy [7].…”

Section: Introductionmentioning

confidence: 99%

AbstractSDRs: Bring Down the Two-Language Barrier With Julia Language for Efficient SDR Prototyping

Lavaud

Gerzaguet

Gautier

et al. 2021

IEEE Embedded Syst. Lett.

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Network slicing - enabled RAN management for 5G: Cross layer control based on SDN and SDR

Cited by 29 publications

References 9 publications

Network Slicing: Recent Advances, Taxonomy, Requirements, and Open Research Challenges

Network Slicing: Recent Advances, Taxonomy, Requirements, and Open Research Challenges

T-S3RA: Traffic-Aware Scheduling for Secure Slicing and Resource Allocation in SDN/NFVEnabled 5G Networks

AbstractSDRs: Bring Down the Two-Language Barrier With Julia Language for Efficient SDR Prototyping

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