A Study of 5G Edge-Central Core Network Split Options

With the wide adoption of edge compute infrastructures, an opportunity has arisen to deploy part of the functionality at the edge of the network to enable a localized connectivity service. This development is also supported by the adoption of “on-premises” local 5G networks addressing the needs of different vertical industries and by new standardized infrastructure services such as Mobile Edge Computing (MEC). This article introduces a comprehensive set of deployment options for the 5G network and its network management, complementing MEC with the connectivity service and addressing different classes of use cases and applications. We have also practically implemented and tested the newly introduced options in the form of slices within a standard-based testbed. Our performed validation proved their feasibility and gave a realistic perspective on their impact. The qualitative assessment of the connectivity service gives a comprehensive overview on which solution would be viable to be deployed for each vertical market and for each large-scale operator situation, making a step forward towards automated distributed 5G deployments.

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A Comprehensive Overview of TCP Congestion Control in 5G Networks: Research Challenges and Future Perspectives

Sensors ◽

10.3390/s21134510 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4510

Author(s):

Josip Lorincz ◽

Zvonimir Klarin ◽

Julije Ožegović

Keyword(s):

Congestion Control ◽

Transmission Control Protocol ◽

Mobile Network ◽

Future Research ◽

Core Network ◽

5G Networks ◽

Comprehensive Overview ◽

Survey Paper ◽

High Penetration ◽

Reliable Communications

In today’s data networks, the main protocol used to ensure reliable communications is the transmission control protocol (TCP). The TCP performance is largely determined by the used congestion control (CC) algorithm. TCP CC algorithms have evolved over the past three decades and a large number of CC algorithm variations have been developed to accommodate various network environments. The fifth-generation (5G) mobile network presents a new challenge for the implementation of the TCP CC mechanism, since networks will operate in environments with huge user device density and vast traffic flows. In contrast to the pre-5G networks that operate in the sub-6 GHz bands, the implementation of TCP CC algorithms in 5G mmWave communications will be further compromised with high variations in channel quality and susceptibility to blockages due to high penetration losses and atmospheric absorptions. These challenges will be particularly present in environments such as sensor networks and Internet of Things (IoT) applications. To alleviate these challenges, this paper provides an overview of the most popular single-flow and multy-flow TCP CC algorithms used in pre-5G networks. The related work on the previous examinations of TCP CC algorithm performance in 5G networks is further presented. A possible implementation of TCP CC algorithms is thoroughly analysed with respect to the specificities of 5G networks, such as the usage of high frequencies in the mmWave spectrum, the frequent horizontal and vertical handovers, the implementation of the 5G core network, the usage of beamforming and data buffering, the exploitation of edge computing, and the constantly transmitted always-on signals. Moreover, the capabilities of machine learning technique implementations for the improvement of TCPs CC performance have been presented last, with a discussion on future research opportunities that can contribute to the improvement of TCP CC implementation in 5G networks. This survey paper can serve as the basis for the development of novel solutions that will ensure the reliable implementation of TCP CC in different usage scenarios of 5G networks.

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Future Generation 5G Wireless Networks for Smart Grid: A Comprehensive Review

Energies ◽

10.3390/en12112140 ◽

2019 ◽

Vol 12 (11) ◽

pp. 2140 ◽

Cited By ~ 20

Author(s):

Sofana Reka. S ◽

Tomislav Dragičević ◽

Pierluigi Siano ◽

S.R. Sahaya Prabaharan

Keyword(s):

Smart Grid ◽

Electricity Markets ◽

Smart Grids ◽

Large Scale ◽

Business Models ◽

Future Generation ◽

Current Status ◽

Complete Analysis ◽

5G Networks ◽

5G Network

Wireless cellular networks are emerging to take a strong stand in attempts to achieve pervasive large scale obtainment, communication, and processing with the evolution of the fifth generation (5G) network. Both the present day cellular technologies and the evolving new age 5G are considered to be advantageous for the smart grid. The 5G networks exhibit relevant services for critical and timely applications for greater aspects in the smart grid. In the present day electricity markets, 5G provides new business models to the energy providers and improves the way the utility communicates with the grid systems. In this work, a complete analysis and a review of the 5G network and its vision regarding the smart grid is exhibited. The work discusses the present day wireless technologies, and the architectural changes for the past years are shown. Furthermore, to understand the user-based analyses in a smart grid, a detailed analysis of 5G architecture with the grid perspectives is exhibited. The current status of 5G networks in a smart grid with a different analysis for energy efficiency is vividly explained in this work. Furthermore, focus is emphasized on future reliable smart grid communication with future roadmaps and challenges to be faced. The complete work gives an in-depth understanding of 5G networks as they pertain to future smart grids as a comprehensive analysis.

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Satellite Integration into 5G: Accent on First Over-The-Air Tests of an Edge Node Concept with Integrated Satellite Backhaul

Future Internet ◽

10.3390/fi11090193 ◽

2019 ◽

Vol 11 (9) ◽

pp. 193 ◽

Cited By ~ 7

Author(s):

Florian Völk ◽

Konstantinos Liolis ◽

Marius Corici ◽

Joe Cahill ◽

Robert T. Schwarz ◽

...

Keyword(s):

Network Architecture ◽

Large Scale ◽

Satellite Networks ◽

Base Stations ◽

Geostationary Orbit ◽

Core Network ◽

5G Networks ◽

Remote Areas ◽

Edge Node ◽

Satellite Integration

The 5G vision embraces a broad range of applications including the connectivity in underserved and remote areas. In particular, for these applications, satellites are going to play a role in future 5G networks to provide capacity on trains, vessels, aircraft, and for base stations around the globe. In this paper, a 5G edge node concept, developed and evaluated with over-the-air tests using satellites in the geostationary orbit, is presented. The article covers a testbed demonstration study in Europe with a large-scale testbed including satellites and the latest standardization for the network architecture. The main goal of this testbed is to evaluate how satellite networks can be best integrated within the convergent 5G environment. The over-the-air tests for 5G satellite integration in this article are based on a 3GPP Release 15 core network architecture.

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Strategic Outsourcing

IT Outsourcing ◽

10.4018/978-1-60566-770-6.ch065 ◽

2010 ◽

pp. 1060-1072 ◽

Cited By ~ 1

Author(s):

Varadharajan Sridhar

Keyword(s):

Network Management ◽

Customer Service ◽

Large Scale ◽

Core Competency ◽

Core Network ◽

It Services ◽

Mobile Operator ◽

Production Economies ◽

Strategic Outsourcing ◽

Management Functions

Telecom operators have a wide variety of functions to perform including marketing of telecom products and services, managing their networks, providing after-sales customer service, and innovating new products and services in tune with fast changing technologies. Though until recently the telcos have kept their core network management functions in-house, there are recent announcements of large scale outsourcing of network management functions. As operators, especially those providing mobile services, have evolved from offering voice services to advanced data and video services, the Information Technology (IT) services required for appropriate management of these vale added service offerings have also become complex. Some carriers have also outsourced their IT functions to large IT services vendors. In this chapter we deliberate the reasons for strategic outsourcing such as core competency, production economies, and transaction costs as presented in the literature and analyze these in the context of outsourcing model pioneered by an Indian mobile operator. We also explain vulnerabilities and risks associated with these outsourcing contracts and measures to be taken by the firm to mitigate their effects.

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Deep Learning at the Mobile Edge: Opportunities for 5G Networks

Applied Sciences ◽

10.3390/app10144735 ◽

2020 ◽

Vol 10 (14) ◽

pp. 4735 ◽

Cited By ~ 3

Author(s):

Miranda McClellan ◽

Cristina Cervelló-Pastor ◽

Sebastià Sallent

Keyword(s):

Large Scale ◽

Edge Computing ◽

Connected Vehicles ◽

Mobile Edge Computing ◽

5G Networks ◽

End User ◽

Network Resources ◽

Mobility Modeling ◽

Novel Applications ◽

Adaptive Resource

Mobile edge computing (MEC) within 5G networks brings the power of cloud computing, storage, and analysis closer to the end user. The increased speeds and reduced delay enable novel applications such as connected vehicles, large-scale IoT, video streaming, and industry robotics. Machine Learning (ML) is leveraged within mobile edge computing to predict changes in demand based on cultural events, natural disasters, or daily commute patterns, and it prepares the network by automatically scaling up network resources as needed. Together, mobile edge computing and ML enable seamless automation of network management to reduce operational costs and enhance user experience. In this paper, we discuss the state of the art for ML within mobile edge computing and the advances needed in automating adaptive resource allocation, mobility modeling, security, and energy efficiency for 5G networks.

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Dehydroepiandrosterone (DHEA) and its Sulphate (DHEAS) in Alzheimer’s Disease

Current Alzheimer Research ◽

10.2174/1567205017666200317092310 ◽

2020 ◽

Vol 17 (2) ◽

pp. 141-157 ◽

Cited By ~ 2

Author(s):

Dubravka S. Strac ◽

Marcela Konjevod ◽

Matea N. Perkovic ◽

Lucija Tudor ◽

Gordana N. Erjavec ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Large Scale ◽

Therapeutic Potential ◽

Relevant Literature ◽

Comprehensive Overview ◽

Brain Functions ◽

Specific Effects ◽

And Behavior

Background: Neurosteroids Dehydroepiandrosterone (DHEA) and Dehydroepiandrosterone Sulphate (DHEAS) are involved in many important brain functions, including neuronal plasticity and survival, cognition and behavior, demonstrating preventive and therapeutic potential in different neuropsychiatric and neurodegenerative disorders, including Alzheimer’s disease. Objective: The aim of the article was to provide a comprehensive overview of the literature on the involvement of DHEA and DHEAS in Alzheimer’s disease. Method: PubMed and MEDLINE databases were searched for relevant literature. The articles were selected considering their titles and abstracts. In the selected full texts, lists of references were searched manually for additional articles. Results: We performed a systematic review of the studies investigating the role of DHEA and DHEAS in various in vitro and animal models, as well as in patients with Alzheimer’s disease, and provided a comprehensive discussion on their potential preventive and therapeutic applications. Conclusion: Despite mixed results, the findings of various preclinical studies are generally supportive of the involvement of DHEA and DHEAS in the pathophysiology of Alzheimer’s disease, showing some promise for potential benefits of these neurosteroids in the prevention and treatment. However, so far small clinical trials brought little evidence to support their therapy in AD. Therefore, large-scale human studies are needed to elucidate the specific effects of DHEA and DHEAS and their mechanisms of action, prior to their applications in clinical practice.

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DeepCog: Cognitive Network Management in Sliced 5G Networks with Deep Learning

IEEE INFOCOM 2019 - IEEE Conference on Computer Communications ◽

10.1109/infocom.2019.8737488 ◽

2019 ◽

Cited By ~ 24

Author(s):

Dario Bega ◽

Marco Gramaglia ◽

Marco Fiore ◽

Albert Banchs ◽

Xavier Costa-Perez

Keyword(s):

Deep Learning ◽

Network Management ◽

5G Networks ◽

Cognitive Network

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Synchronization in 5G networks: a hybrid Bayesian approach toward clock offset/skew estimation and its impact on localization

EURASIP Journal on Wireless Communications and Networking ◽

10.1186/s13638-021-01963-x ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Meysam Goodarzi ◽

Darko Cvetkovski ◽

Nebojsa Maletic ◽

Jesús Gutiérrez ◽

Eckhard Grass

Keyword(s):

Bayesian Approach ◽

Large Scale ◽

Hybrid Approach ◽

Position Estimation ◽

5G Networks ◽

Clock Skew ◽

Depth Analysis ◽

The Impact ◽

Mean Square Errors ◽

Clock Offset

AbstractClock synchronization has always been a major challenge when designing wireless networks. This work focuses on tackling the time synchronization problem in 5G networks by adopting a hybrid Bayesian approach for clock offset and skew estimation. Furthermore, we provide an in-depth analysis of the impact of the proposed approach on a synchronization-sensitive service, i.e., localization. Specifically, we expose the substantial benefit of belief propagation (BP) running on factor graphs (FGs) in achieving precise network-wide synchronization. Moreover, we take advantage of Bayesian recursive filtering (BRF) to mitigate the time-stamping error in pairwise synchronization. Finally, we reveal the merit of hybrid synchronization by dividing a large-scale network into local synchronization domains and applying the most suitable synchronization algorithm (BP- or BRF-based) on each domain. The performance of the hybrid approach is then evaluated in terms of the root mean square errors (RMSEs) of the clock offset, clock skew, and the position estimation. According to the simulations, in spite of the simplifications in the hybrid approach, RMSEs of clock offset, clock skew, and position estimation remain below 10 ns, 1 ppm, and 1.5 m, respectively.

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