5G IoT Industry Verticals and Network Requirements

Condoluci, Massimo; Rosas, María Ángel Lema; Mahmoodi, Toktam; Dohler, Mischa

doi:10.4018/978-1-5225-2799-2.ch006

Cited by 16 publications

(15 citation statements)

References 27 publications

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“…The 5G network is the best solution for this scenario [13,14], which also makes it possible to incorporate the remote control of robots: according to this model, in a cloud environment, rather than in the robot itself, various functions aimed at regulating motion can be stored. It is thus assumed that the security of the networks in which the control modules work from cyber attacks is of vital importance.…”

Section: Case Study and Resultsmentioning

confidence: 99%

Resilience in Critical Infrastructures: The Role of Modelling and Simulation

Foglietta¹,

Panzieri²

2021

Issues on Risk Analysis for Critical Infrastructure Protection

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Resilience and risk are fundamental concepts for critical infrastructure protection, but it is complex to assess them. Modelling critical infrastructure interdependency helps in evaluating the resilience and risk metrics. We propose the MHR approach as a road-map to model infrastructures and it is implemented using CISIApro 2.0. MHR suggests considering three different layers in each infrastructure: holistic, service and reductionist agents. In this chapter, this framework has been tested in a scenario made of a modern telecommunication network, a hospital ward and a smart factory. The scenario takes into account cyber attacks and their consequences on the components, services and holistic nodes. The proposed framework is under validation within the EU H2020 RESISTO project with good results and in various test-beds.

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Section: Case Study and Resultsmentioning

confidence: 99%

Resilience in Critical Infrastructures: The Role of Modelling and Simulation

Foglietta¹,

Panzieri²

2021

Issues on Risk Analysis for Critical Infrastructure Protection

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“…As the 5G era begins, Network Slicing is being presented as the mechanism for addressing different enterprise requirements, and unlocking commercial opportunities for service providers [2]. Network Slicing promises to deliver a D-QoS in 5G networks by implementing several logical/virtual networks on top of a single 5G network infrastructure [3].…”

Section: Lessons For 5g Network Slicingmentioning

confidence: 99%

“…Its core idea is to create logical networks over the same physical infrastructure and to then customize and isolate these logical networks according to the requirements of each slice (e.g. different use cases, tenant, virtual operator, etc) [2]. Consequently, from a business perspective, Network Slicing is a means to provide different experiences to different customers, making it similar to classic D-QoS mechanisms.…”

Section: Introductionmentioning

confidence: 99%

From ATM to MPLS and QCI: The Evolution of Differentiated QoS Standards and Implications for 5G Network Slicing

Obiodu

Sastry

2020

IEEE Comm. Stand. Mag.

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The networking community continues to create new technologies, and update existing ones to improve the quality, reliability and 'tailorability' of data networks. However, whenever Internet Service Providers (ISPs) attempt to productize 'tailorability' and sell it explicitly to end customers as a premium service over the 'best effort' connectivity, they either fail to overcome net neutrality concerns, or struggle to gain market traction. For this article, we focus only on those networking protocols, technologies or standards whose goal is to offer tailored connectivity to paying customers on a public network and refer to them as Differentiated QoS (D-QoS) standards. This article makes two contributions to the understanding of the goals of D-QoS standards. First, it explores their techno-economic market trajectory to understand the factors that determine success. In doing this, we acknowledge that, while there is wide variation and dissimilarity in their underlying technical properties, the expectation and goal for all D-QoS standards is that they will be used to provide a guaranteed connection that customers could be prepared to pay for. As such, we consider transport layer technologies (e.g. ATM, Frame Relay, MPLS), signaling technologies (e.g. RSVP), data packet markers (e.g. IP ToS, DiffServ, WME, QCI), and end-toend separation solutions (e.g. Leased lines, Network Slicing) as a single cohort and analyse them together. Second, by exploring the parallels with 5G Network Slicing, we argue that despite its inherent technical differences with other D-QoS standards, the commercial performance of Network Slicing may end up resembling that of previous D-QoS standards. Consequently, we seek to learn lessons from previous D-QoS attempts and suggest that enterprise-focused 5G slices, running within a single service provider's domain and with binding service level agreements, will have the highest chance of success in the short/medium term.

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“…The support for a massive number of internet of things (IoT) devices is a substantial requirement for the 5G of mobile networks [6,7]. As a consequence, the dense deployment of a massive number of devices increases the experienced interference.…”

Section: Preliminariesmentioning

confidence: 99%

Resource Allocation Combining Heuristic Matching and Particle Swarm Optimization Approaches: The Case of Downlink Non-Orthogonal Multiple Access

Pliatsios

Sarigiannidis

2019

Information

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The ever-increasing requirement of massive connectivity, due to the rapid deployment of internet of things (IoT) devices, in the emerging 5th generation (5G) mobile networks commands for even higher utilization of the available spectrum. Non-orthogonal multiple access (NOMA) is a promising solution that can effectively accommodate a higher number of users, resulting in increased spectrum utilization. In this work, we aim to maximize the total throughput of a NOMA system, while maintaining a good level of fairness among the users. We propose a three-step method where the first step matches the users to the channels using a heuristic matching algorithm, while the second step utilizes the particle swarm optimization algorithm to allocate the power to each channel. In the third step, the power allocated to each channel is further distributed to the multiplexed users based on their respective channel gains. Based on extensive performance simulations, the proposed method offers notable improvement, e.g., 15% in terms of system throughput and 55% in terms of user fairness.

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5G IoT Industry Verticals and Network Requirements

Abstract: The effective provisioning of industry verticals over the next-to-come 5G systems

Cited by 16 publications

References 27 publications

Resilience in Critical Infrastructures: The Role of Modelling and Simulation

Resilience in Critical Infrastructures: The Role of Modelling and Simulation

From ATM to MPLS and QCI: The Evolution of Differentiated QoS Standards and Implications for 5G Network Slicing

Resource Allocation Combining Heuristic Matching and Particle Swarm Optimization Approaches: The Case of Downlink Non-Orthogonal Multiple Access

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