Cloud Native 5G Virtual Network Functions: Design Principles and Use Cases

Imadali, Sofiane; Bousselmi, Ayoub

doi:10.1109/sc2.2018.00019

Cited by 25 publications

(16 citation statements)

References 8 publications

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“…In the next few years, network operators will tend towards cloud architectures [107] in both edge and core network [108], to increase efficiency, reliability, and scalability. Cloudnative is the process of transitioning software deployments from traditional infrastructure to software and API-enabled infrastructure to leverage automation and DevOps techniques.…”

Section: Cnf Placementmentioning

confidence: 99%

VNF and CNF Placement in 5G: Recent Advances and Future Trends

Attaoui¹,

Sabir

Elbiaze

et al. 2023

IEEE Trans. Netw. Serv. Manage.

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With the growing demand for openness, scalability, and granularity, mobile network function virtualization (NFV) has emerged as a key enabler for the most of mobile network operators. NFV decouples network functions from hardware devices. This decoupling allows network services, called Virtualized Network Functions (VNFs), to be hosted on commodity hardware which simplifies and enhances service deployment and management for providers, improves flexibility, and leads to efficient and scalable resource usage, and lower costs. The proper placement of VNFs in the hosting infrastructures is one of the main technical challenges. This placement significantly influences the network's performance, reliability, and operating costs. The VNF placement is NP-Hard. Therefore, there is a need for placement methods that can cope with the complexity of the problem and find appropriate solutions in a reasonable duration. The primary purpose of this study is to provide a taxonomy of optimization techniques used to tackle the VNF placement problems. We classify the studied papers based on performance metrics, methods, algorithms, and environment. Virtualization is not limited to simply replacing physical machines with virtual machines or VNFs, but may also include microservices, containers, and cloud-native systems. In this context, the second part of our article focuses on the placement of Containers Network Functions (CNFs) in edge/fog computing. Many issues have been considered as traffic congestion, resource utilization, energy consumption, performance degradation, etc. For each matter, various solutions are proposed through different surveys and research papers in which each one addresses the placement problem in a specific manner by suggesting single objective or multi-objective methods based on different types of algorithms such as heuristic, meta-heuristic, and machine learning algorithms.

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Section: Cnf Placementmentioning

confidence: 99%

VNF and CNF Placement in 5G: Recent Advances and Future Trends

Attaoui¹,

Sabir

Elbiaze

et al. 2023

IEEE Trans. Netw. Serv. Manage.

View full text Add to dashboard Cite

show abstract

“…In one scenario, the telecommunication industry will enable Content Providers to place VNFs into the networks that connect their data centers and their customers. Other works have applied the cloud-native principles to 5G systems [7], [8]. In [8], the authors provided a proof of concept for 5G network slicing.…”

Section: B Related Workmentioning

confidence: 99%

“…The SFCs would represent an abstraction of a network function or capability, such as network authentication or packet scheduling. While [7] proposes to shift Virtual Machine (VM) based VNFs toward container based ones to achieve more lightweight virtualization. This approach, called native-cloud VNF, is meant to provide 5GaaS.…”

Section: B Related Workmentioning

confidence: 99%

AI-Based Resource Management in Beyond 5G Cloud Native Environment

et al. 2021

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5G system and beyond targets a gigantic number of emerging applications and services that will create an extra overhead on the network traffic. Moreover, these industrial verticals have aggressive, contentious, and conflicting requirements that make the network have an arduous mission for achieving the desired objectives. It is expected to get requirements with close to zero time latency, high data rate, and network reliability. Fortunately, a ray of hope comes shining the way of telecom providers with the new progress and achievements in machine learning, cloud computing, micro-services, and the ETSI Zerotouch network and Service Management (ZSM) era. For this reason there is a colossal impetus from industries and academia towards applying these techniques by creating a new concept called Cognitive Cloud Native environment that can cohabit and adapt according to the network and resource state, and perceived Key Performance Indicators (KPIs). In this paper, we pursue the aforementioned concept by providing a unified hierarchical closed-loop network and service management framework that can meet the desired objectives. Also, we have proposed a cloud-native simulator that accurately mimics cloud-native environments, and enables us to quickly evaluate new frameworks and ideas. The simulation results demonstrate the efficiency of our simulator for parroting the real testbeds in various metrics.

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“…A considerable amount of work is mainly divided between different solutions to orchestrate NFVs in a dedicated cloud architecture presented in papers [12], [21] and virtualized functions developed for 4G and 5G mobile core. Table I summarizes the existing OSS projects mainly dedicated to the virtualization of mobile packet core according to the 4G specifications and shows few initiatives for the development of NFs for 5G SBA.…”

Section: Related Workmentioning

confidence: 99%

“…Even though a central cloud offers the availability of powerful computation and storage resources, it can generate significant delay when it comes to intensive processing operations. On the other hand, the edge cloud is very often in the proximity of the Radio Access Network (RAN) which leads to a decrease in delay and jitter, but with limited computation and storage capacity [21]. Cisco introduced in 2012 a new paradigm called "fog computing" in order to reduce the burden of transferring data from the central cloud to the edge network [22].…”

Section: Introductionmentioning

confidence: 99%

Collaborative Cloud - Edge: A Declarative API orchestration model for the NextGen 5G Core

Ungureanu

Vlădeanu

Kooij

2021

2021 IEEE International Conference on Service-Oriented System Engineering (SOSE)

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As the edge computing era matures, it encompasses a broader range of applications that will be able to opportunistically use both the edge and the cloud mainly determined by the location constraints or the mission-critical reasons. Moreover, the convergence of verticals with the next generation mobile network will lead to an imminent edge-cloud collaboration that needs to be carefully addressed by Mobile Network Operators (MNOs). This paper proposes a novel approach to orchestrate the next-generation 5G core running as Cloud-Native Network Functions (CNFs) closer to the edge network while offloading the computation power required to ensure on-demand processing to a central cloud infrastructure. In this manner, full service isolation and network segmentation can be achieved independently from the geographical region with a high degree of scalability. Our main objective is to automate the CNFs provisioning in a declarative API-style in order to easily manage the deployment of applications and services across multiple clusters. Therefore, in our setup we considered crucial to assess the benefits of running the 5G Service-Based Architecture (SBA) in the cloud with multitenancy capabilities and evaluate the performance in terms of latency, while keeping the network control at the edge.

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Cloud Native 5G Virtual Network Functions: Design Principles and Use Cases

Cited by 25 publications

References 8 publications

VNF and CNF Placement in 5G: Recent Advances and Future Trends

VNF and CNF Placement in 5G: Recent Advances and Future Trends

AI-Based Resource Management in Beyond 5G Cloud Native Environment

Collaborative Cloud - Edge: A Declarative API orchestration model for the NextGen 5G Core

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