Understanding QoS Applicability in 5G Transport Networks

Cominardi, Luca; Contreras, Luis M.; Bcrnardos, Carlos J.; Berberana, Ignacio

doi:10.1109/bmsb.2018.8436847

Cited by 31 publications

(21 citation statements)

References 4 publications

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“…The particular characterization of the services into categories, such as eMBB or uRLLC, remarks that some parameters can be relaxed or can be seen as less critical from one service respect to the other, even falling on the same service type, an aspect exploited in this work. Some other studies have also revealed this fact when dealing for instance, with the QoS capabilities to be offered by the network [20].…”

Section: Discussionmentioning

confidence: 83%

Computing at the Edge: But, what Edge?

Contreras

Baliosian

Martínez-Juliá

et al. 2020

NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium

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The traditional telecommunications business is evolving towards offering a richer set of services beyond basic connectivity, leveraging on network programmability and virtualization. A versatile execution environment is required, capable of running different workloads in different locations in the network. Cloud computing is the key paradigm that allows fostering this trending change. One interesting question to solve is to what extent those computing environments have to move towards the edge. Some services can be enabled by environments with increased capillarity, while others can be implemented in environments with more relaxed constraints (e.g., in terms of latency). This paper explores this topic by differentiating service edge from physical network edge and proposing an architecture based on the ALTO server for assisting orchestration systems in discriminating the suitable environments for each service. In addition to that, we propose a network-flow based strategy for assigning service functions to infrastructure elements following those precepts, together with an initial validation on the scalability of the assignation solution, a well-known problem of this task.

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Section: Discussionmentioning

confidence: 83%

Computing at the Edge: But, what Edge?

Contreras

Baliosian

Martínez-Juliá

et al. 2020

NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium

Self Cite

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“…For the public network infrastructure, a 5G transport network is assumed based on [6] and [7]. All the RUs present in the use case transmit their traffic up to an access ring composed of several switches connected in a ring fashion.…”

Section: Use Case: Mobile Roboticsmentioning

confidence: 99%

Delay and Reliability-Constrained VNF Placement on Mobile and Volatile 5G Infrastructure

Németh¹,

Molner

Martín‐Pérez

et al. 2022

IEEE Trans. on Mobile Comput.

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Ongoing research and industrial exploitation of SDN and NFV technologies promise higher flexibility on network automation and infrastructure optimization. Choosing the location of Virtual Network Functions is a central problem in the automation and optimization of the software-defined, virtualization-based next generation of networks such as 5G and beyond. Network services provided for autonomous vehicles, factory automation, e-health and cloud robotics often require strict delay bounds and reliability constraints influenced by the location of its composing Virtual Network Functions. Robots, vehicles and other end-devices provide significant capabilities such as actuators, sensors and local computation which are essential for some services. Moreover, these devices are continuously on the move and might lose network connection or run out of battery, which further challenge service delivery in this dynamic environment. This work tackles the mobility, and battery restrictions; as well as the temporal aspects and conflicting traits of reliable, low latency service deployment over a volatile network, where mobile compute nodes act as an extension of the cloud and edge computing infrastructure. The problem is formulated as a costminimizing Virtual Network Function placement optimization and an efficient heuristic is proposed. The algorithms are extensively evaluated from various aspects by simulation on detailed real-world scenarios.

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“…Furthermore, the normalized revenues associated to the gold, silver, and bronze graphs are: [5,3,2] for grid monitoring, [4, 2, 1] for bird's eye, and [3, 2, 1] for industrial robotics. The physical infrastructure is composed of six hosts (servers) connected in a two-layer topology reflecting the core network organization used in [15]. For simplicity, we focus on computational capabilities alone and vary the normalized CPU available at each host between 1 and 5.…”

Section: Performance Evaluationmentioning

confidence: 99%

Service Shifting: A Paradigm for Service Resilience in 5G

Malandrino¹,

Chiasserini²,

Landi

2019

IEEE Commun. Mag.

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Many real-world services can be provided through multiple virtual network function (VNF) graphs, corresponding, e.g., to high-and low-complexity variants of the service itself. Based on this observation, we extend the concept of service scaling in network orchestration to service shifting, i.e., upgrading or downgrading the VNF graph to use among those implementing the same service. Service shifting can serve multiple goals, from reducing operational costs to reacting to infrastructure problems. Furthermore, it enhances the flexibility of service-level agreements between network operators and third party content providers ("verticals"). In this paper, we introduce and describe the service shifting concept, its benefits, and the associated challenges, with special reference to how service shifting can be integrated within real-world 5G architectures and implementations. We conclude that existing network orchestration frameworks can be easily extended to support service shifting, and its adoption has the potential to make 5G network slices easier for the operators to manage under high-load conditions, while still meeting the verticals' requirements.

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Understanding QoS Applicability in 5G Transport Networks

Cited by 31 publications

References 4 publications

Computing at the Edge: But, what Edge?

Computing at the Edge: But, what Edge?

Delay and Reliability-Constrained VNF Placement on Mobile and Volatile 5G Infrastructure

Service Shifting: A Paradigm for Service Resilience in 5G

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