Agile management of 5G core network based on SDN/NFV technology

Choi, Taesang; Kim, TaeYeon; Tavernier, Wouter; Korvala, Aki; Pajunpaa, Jussi

doi:10.1109/ictc.2017.8190795

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…Dexterous administration was as of late evolved by a 5G-based SDN/NFV design and executed in a proof of idea (PoC) for the Pyeongchang Winter Olympics [22]. The accompanying qualities, like openness, area mindfulness, higher organization transmission capacity, and super low dormancy, were of foremost significance in this engineering: It incorporated a few auto-scaling cycles like MANO, MANO/SDN, vEPC, VNFM, and so forth.…”

Section: G Architecturementioning

confidence: 99%

SDN/NFV architectures for edge-cloud oriented IoT

Jaadouni

Saadi²,

Chaoui

2022

ITM Web Conf.

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Thanks to Software Defined Networking (SDN) and Network Functions Virtualization (NFV), the use and behaviour of interconnect network backhauls to provide virtualization services has changed completely. Several benefits have been discovered in various application areas that combine SDN and NFV. As a result, we explored the SDN / NFV paradigm to determine if network services could be efficiently deployed, managed, and distributed to end users. The Internet of Things (IoT) is inseparable from improving SDN / b NFV to improve this task. However, until now, problems related to Edge cloud communications and network services have not been effectively mitigated. The rest of this article is organized as follows. We first present the background of this work. Then we present the new technologies around these topics and the extended architecture, and e. Finally, we conclude this work.

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Section: G Architecturementioning

confidence: 99%

SDN/NFV architectures for edge-cloud oriented IoT

Jaadouni

Saadi²,

Chaoui

2022

ITM Web Conf.

View full text Add to dashboard Cite

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“…In addition, an optical network architecture is proposed and investigated in this paper to provide the wired infrastructural needed in 5G networks, and to support NFV and content caching. In the literature, NFV was investigated either in mobile core networks [14]- [16] or in the radio access network [17]- [19] of the mobile network and mostly using pooling of resources such as the work in [20], [21]. In contrast, virtualization in this paper is not limited to a certain part in the mobile network, but is applied in both the mobile core network and the radio access network.…”

Section: Introductionmentioning

confidence: 99%

Optimized Energy Aware 5G Network Function Virtualization

et al. 2019

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In this paper, network function virtualization (NFV) is identified as a promising key technology, which can contribute to energy-efficiency improvement in 5G networks. An optical network supported architecture is proposed and investigated in this paper to provide the wired infrastructure needed in 5G networks and to support NFV toward an energy efficient 5G network. In this paper, the mobile core network functions, as well as baseband function, are virtualized and provided as VMs. The impact of the total number of active users in the network, backhaul/fronthaul configurations, and VM inter-traffic are investigated. A mixed integer linear programming (MILP) optimization model is developed with the objective of minimizing the total power consumption by optimizing the VMs location and VMs servers' utilization. The MILP model results show that virtualization can result in up to 38% (average 34%) energy saving. The results also reveal how the total number of active users affects the baseband virtual machines (BBUVMs) optimal distribution whilst the core network virtual machines (CNVMs) distribution is affected mainly by the inter-traffic between the VMs. For real-time implementation, two heuristics are developed, an energy efficient NFV without CNVMs inter-traffic (EENFVnoITr) heuristic and an energy efficient NFV with CNVMs inter-traffic (EENFVwithITr) heuristic, both produce comparable results to the optimal MILP results. Finally, a genetic algorithm is developed for further verification of the results.

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“…For example, a subset of VNFs may come with location constraints. In this case, some VNFs must be deployed at the reliable and more resource powerful Cloud Computing layer (e.g., video optimization, deep packet inspection [15]), while others need to be instantiated close to the end users at the MEC (e.g., network address translation-NAT, firewall, traffic prioritazion) [4,16].…”

Section: Introductionmentioning

confidence: 99%

VNF Placement Optimization at the Edge and Cloud †

et al. 2019

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Network Function Virtualization (NFV) has revolutionized the way network services are offered to end users. Individual network functions are decoupled from expensive and dedicated middleboxes and are now provided as software-based virtualized entities called Virtualized Network Functions (VNFs). NFV is often complemented with the Cloud Computing paradigm to provide networking functions to enterprise customers and end-users remote from their premises. NFV along with Cloud Computing has also started to be seen in Internet of Things (IoT) platforms as a means to provide networking functions to the IoT traffic. The intermix of IoT, NFV, and Cloud technologies, however, is still in its infancy creating a rich and open future research area. To this end, in this paper, we propose a novel approach to facilitate the placement and deployment of service chained VNFs in a network cloud infrastructure that can be extended using the Mobile Edge Computing (MEC) infrastructure for accommodating mission critical and delay sensitive traffic. Our aim is to minimize the end-to-end communication delay while keeping the overall deployment cost to minimum. Results reveal that the proposed approach can significantly reduce the delay experienced, while satisfying the Service Providers' goal of low deployment costs.

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Agile management of 5G core network based on SDN/NFV technology

Cited by 3 publications

References 2 publications

SDN/NFV architectures for edge-cloud oriented IoT

SDN/NFV architectures for edge-cloud oriented IoT

Optimized Energy Aware 5G Network Function Virtualization

VNF Placement Optimization at the Edge and Cloud †

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