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

Sensors ◽  
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.

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

Network ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 354-368
Author(s):  
Marius Corici ◽  
Pousali Chakraborty ◽  
Thomas Magedanz
Keyword(s):  
Network Management ◽  
Large Scale ◽  
Qualitative Assessment ◽  
Mobile Edge Computing ◽  
Core Network ◽  
5G Networks ◽  
Comprehensive Overview ◽  
5G Network ◽  
Infrastructure Services ◽  
Vertical Market

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.

5G Networks

2019 ◽  
pp. 37-70 ◽  
Author(s):  
Noman Islam ◽  
Ainuddin Wahid Abdul Wahab
Keyword(s):  
Mobile Communication ◽  
Mobile Network ◽  
Future Research ◽  
5G Networks ◽  
Holistic View ◽  
Research Issues ◽  
Enabling Technologies ◽  
5G Network ◽  
New Generation ◽  
Roll Out

Mobile communication witnesses a new generation after every 10 years. Following the same trend, the roll out of next generation called 5G network is anticipated by 2020. In this chapter, a critical review of enabling technologies and research issues of 5G network is provided. The novelty of the chapter lies in providing a holistic view of 5G networks spanning discussions on technologies and issues across all the layers of protocol stack. Specifically, the chapter talks about the higher-level research issues of 5G network. The chapter is primarily structured as follows: It starts with a brief overview of various generations of mobile communication. Then, the problems with existing generation of mobile communication are presented, thus providing the motivation for a new generation of mobile network. A survey of different enabling technologies of 5G network is provided afterwards. After having brief discussions on key enablers, the chapter presents various research issues of 5G network. The chapter concludes with highlighting current challenges and future research issues.

scholarly journals 5G and the Need for Platform Integrity

2020 ◽  
pp. 15-28
Author(s):  
Alec Brusilovsky ◽  
Ira McDonald
Keyword(s):  
Mobile Network ◽  
Core Network ◽  
5G Networks ◽  
Network Nodes ◽  
Rich Diversity ◽  
Authentication And Authorization ◽  
Access Authentication ◽  
Network Transformation ◽  
Cloud Network ◽  
Mobile Network Operators

Current cellular architecture will not be suitable for 5G because it will not scale to the anticipated number of connected endpoints and their rich diversity. The distribution of the previously centralized Core Network (CN) functionality, e.g., Access Authentication and Authorization, has to be decentralized, leading to the demise of the most utilized tool of network security engineering, Physical Security Perimeter. The asserted and attested Platform Integrity of the network nodes that comprise the edges of the network, the network cloud, “network fog”, and the endpoints will allow mobile network operators (MNOs) to create Virtual Network Perimeters and allow highly reliable, diverse, and flexible 5G networks. This article describes the reasons for such network transformation, provides references to applicable standardization activities, and uses the examples of support for Unmanned Aerial Vehicles (UAV) and connected automobiles by 5G networks to justify the need for Platform Integrity.

5G Networks

2021 ◽  
pp. 708-741
Author(s):  
Noman Islam ◽  
Ainuddin Wahid Abdul Wahab
Keyword(s):  
Mobile Communication ◽  
Mobile Network ◽  
Future Research ◽  
5G Networks ◽  
Holistic View ◽  
Research Issues ◽  
Enabling Technologies ◽  
5G Network ◽  
New Generation ◽  
Roll Out

Mobile communication witnesses a new generation after every 10 years. Following the same trend, the roll out of next generation called 5G network is anticipated by 2020. In this chapter, a critical review of enabling technologies and research issues of 5G network is provided. The novelty of the chapter lies in providing a holistic view of 5G networks spanning discussions on technologies and issues across all the layers of protocol stack. Specifically, the chapter talks about the higher-level research issues of 5G network. The chapter is primarily structured as follows: It starts with a brief overview of various generations of mobile communication. Then, the problems with existing generation of mobile communication are presented, thus providing the motivation for a new generation of mobile network. A survey of different enabling technologies of 5G network is provided afterwards. After having brief discussions on key enablers, the chapter presents various research issues of 5G network. The chapter concludes with highlighting current challenges and future research issues.

scholarly journals Organizational Commitment and Lean Sustainability: Literature Review and Directions for Future Research

2021 ◽  
Vol 13 (6) ◽  
pp. 3357 ◽  
Author(s):  
Amal Benkarim ◽  
Daniel Imbeau
Keyword(s):  
Organizational Commitment ◽  
Literature Review ◽  
Lean Manufacturing ◽  
Affective Commitment ◽  
Management Practices ◽  
Employee Commitment ◽  
Future Research ◽  
Comprehensive Overview ◽  
Narrative Literature Review ◽  
Key Aspects

The vast majority of works published on Lean focus on the evaluation of tools and/or the strategies needed for its implementation. Although many authors highlight the degree of employee commitment as one of the key aspects of Lean, what has gone largely unnoticed in the literature, is that few studies have examined in-depth the concept of organizational commitment in connection with Lean. With this narrative literature review article, our main objective is (1) to identify and analyze an extensive body of literature that addresses the Lean Manufacturing approach and how it relates to employee commitment, emphasizing affective commitment as the main type of organizational commitment positively associated with Lean, and (2) to highlight the management practices required to encourage this kind of commitment and promote the success and sustainability of Lean. This paper aims to provide a comprehensive overview that can help researchers and practitioners interested in Lean better understand the importance of employee commitment in this type of approach, and as well, to identify related research questions.

scholarly journals Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 1022
Author(s):  
Hoang T. Nguyen ◽  
Kate T. Q. Nguyen ◽  
Tu C. Le ◽  
Guomin Zhang
Keyword(s):  
Artificial Intelligence ◽  
Flame Retardancy ◽  
Material Science ◽  
Construction Materials ◽  
Engineering Problem ◽  
Future Research ◽  
Fire Performance ◽  
Structural Components ◽  
Comprehensive Overview ◽  
Fire Engineering

The evaluation and interpretation of the behavior of construction materials under fire conditions have been complicated. Over the last few years, artificial intelligence (AI) has emerged as a reliable method to tackle this engineering problem. This review summarizes existing studies that applied AI to predict the fire performance of different construction materials (e.g., concrete, steel, timber, and composites). The prediction of the flame retardancy of some structural components such as beams, columns, slabs, and connections by utilizing AI-based models is also discussed. The end of this review offers insights on the advantages, existing challenges, and recommendations for the development of AI techniques used to evaluate the fire performance of construction materials and their flame retardancy. This review offers a comprehensive overview to researchers in the fields of fire engineering and material science, and it encourages them to explore and consider the use of AI in future research projects.

scholarly journals Endocrine Disrupting Chemicals and Thyroid Cancer: An Overview

Toxics ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 14
Author(s):  
Mathilda Alsen ◽  
Catherine Sinclair ◽  
Peter Cooke ◽  
Kimia Ziadkhanpour ◽  
Eric Genden ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Flame Retardants ◽  
Endocrine Disrupting Chemicals ◽  
National Institutes Of Health ◽  
Future Research ◽  
National Library ◽  
Comprehensive Overview ◽  
Carcinogenic Effect ◽  
Increased Risk ◽  
Endocrine Disrupting

Endocrine disruptive chemicals (EDC) are known to alter thyroid function and have been associated with increased risk of certain cancers. The present study aims to provide a comprehensive overview of available studies on the association between EDC exposure and thyroid cancer. Relevant studies were identified via a literature search in the National Library of Medicine and National Institutes of Health PubMed as well as a review of reference lists of all retrieved articles and of previously published relevant reviews. Overall, the current literature suggests that exposure to certain congeners of flame retardants, polychlorinated biphenyls (PCBs), and phthalates as well as certain pesticides may potentially be associated with an increased risk of thyroid cancer. However, future research is urgently needed to evaluate the different EDCs and their potential carcinogenic effect on the thyroid gland in humans as most EDCs have been studied sporadically and results are not consistent.

SNF1-related protein kinase 1: the many-faced signaling hub regulating developmental plasticity in plants

2021 ◽  
Author(s):  
Muhammed Jamsheer K ◽  
Manoj Kumar ◽  
Vibha Srivastava
Keyword(s):  
Protein Kinase ◽  
Environmental Conditions ◽  
Protein Trafficking ◽  
Developmental Plasticity ◽  
Inositol Phosphate ◽  
Future Research ◽  
Primary Metabolism ◽  
Related Protein ◽  
Comprehensive Overview ◽  
Cellular Processes

AbstractThe Snf1-related protein kinase 1 (SnRK1) is the plant homolog of the heterotrimeric AMP-activated protein kinase/sucrose non-fermenting 1 (AMPK/Snf1), which works as a major regulator of growth under nutrient-limiting conditions in eukaryotes. Along with its conserved role as a master regulator of sugar starvation responses, SnRK1 is involved in controlling the developmental plasticity and resilience under diverse environmental conditions in plants. In this review, through mining and analyzing the interactome and phosphoproteome data of SnRK1, we are highlighting its role in fundamental cellular processes such as gene regulation, protein synthesis, primary metabolism, protein trafficking, nutrient homeostasis, and autophagy. Along with the well-characterized molecular interaction in SnRK1 signaling, our analysis highlights several unchartered regions of SnRK1 signaling in plants such as its possible communication with chromatin remodelers, histone modifiers, and inositol phosphate signaling. We also discuss potential reciprocal interactions of SnRK1 signaling with other signaling pathways and cellular processes, which could be involved in maintaining flexibility and homeostasis under different environmental conditions. Overall, this review provides a comprehensive overview of the SnRK1 signaling network in plants and suggests many novel directions for future research.

Hierarchical Reinforcement Learning

2021 ◽  
Vol 54 (5) ◽  
pp. 1-35
Author(s):  
Shubham Pateria ◽  
Budhitama Subagdja ◽  
Ah-hwee Tan ◽  
Chai Quek
Keyword(s):  
Reinforcement Learning ◽  
Future Research ◽  
Comprehensive Overview ◽  
Open Problems ◽  
Practical Applications ◽  
Hierarchical Reinforcement Learning ◽  
The Past ◽  
Agent Learning ◽  
Multi Agent ◽  
Supplementary Material

Hierarchical Reinforcement Learning (HRL) enables autonomous decomposition of challenging long-horizon decision-making tasks into simpler subtasks. During the past years, the landscape of HRL research has grown profoundly, resulting in copious approaches. A comprehensive overview of this vast landscape is necessary to study HRL in an organized manner. We provide a survey of the diverse HRL approaches concerning the challenges of learning hierarchical policies, subtask discovery, transfer learning, and multi-agent learning using HRL. The survey is presented according to a novel taxonomy of the approaches. Based on the survey, a set of important open problems is proposed to motivate the future research in HRL. Furthermore, we outline a few suitable task domains for evaluating the HRL approaches and a few interesting examples of the practical applications of HRL in the Supplementary Material.

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