scholarly journals Network slicing: a next generation 5G perspective

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Prashant Subedi ◽  
Abeer Alsadoon ◽  
P. W. C. Prasad ◽  
Sabih Rehman ◽  
Nabil Giweli ◽  
...  
Keyword(s):  
Network Architecture ◽  
High Speed ◽  
System Capacity ◽  
Fourth Generation ◽  
Virtual Networks ◽  
Multiple Use ◽  
Network Slicing ◽  
Network Function ◽  
5G Network ◽  
Generation Network

AbstractFifth-generation (5G) wireless networks are projected to bring a major transformation to the current fourth-generation network to support the billions of devices that will be connected to the Internet. 5G networks will enable new and powerful capabilities to support high-speed data rates, better connectivity and system capacity that are critical in designing applications in virtual reality, augmented reality and mobile online gaming. The infrastructure of a network that can support stringent application requirements needs to be highly dynamic and flexible. Network slicing can provide these dynamic and flexible characteristics to a network architecture. Implementing network slicing in 5G requires domain modification of the preexisting network architecture. A network slicing architecture is proposed for an existing 5G network with the aim of enhancing network dynamics and flexibility to support modern network applications. To enable network slicing in a 5G network, we established the virtualisation of the underlying physical 5G infrastructure by utilising technological advancements, such as software-defined networking and network function virtualisation. These virtual networks can fulfil the requirement of multiple use cases as required by creating slices of these virtual networks. Thus, abstracting from the physical resources to create virtual networks and then applying network slicing on these virtual networks enable the 5G network to address the increased demands for high-speed communication.

scholarly journals Dynamic 5G Network Slicing

2021 ◽  
Vol 10 (2) ◽  
pp. 1006-1010
Keyword(s):  
Online Algorithm ◽  
Network Virtualization ◽  
Virtual Network ◽  
Prediction Algorithm ◽  
Network Slicing ◽  
Traffic Demand ◽  
Network Function ◽  
5G Network ◽  
Different Types ◽  
Virtual Network Function

5G network slicing is the use of network virtualization to divide single network connections into multiple distinct virtual connections that provide different amounts of resources to different types of traffic. A 5G NS (Network Slicing) instance is composed of a set of virtual network function (VNF) instances to form the end-to-end (E2E) virtual network for the slice to operate independently. The deployment of a NS is a typical virtual network embedding (VNE) problem. The proposed algorithm consists of three parts. First, we devise a Holt-Winters (HW) prediction algorithm to determine traffic demand for network slices. This method is intended to avoid frequent changes in network topology. Second, we propose a virtual network function (VNF) adaptive scaling strategy to reasonably determine the number of VNFs and resources required for network slices to avoid resource wastage. Finally, we develop a proactive online algorithm to deploy network slices.

scholarly journals Resource Allocation in 4G and 5G Networks: A Review

2021 ◽  
Vol 13 (3) ◽  
Author(s):  
Lavanya-Nehan Degambur ◽  
Avinash Mungur ◽  
Sheeba Armoogum ◽  
Sameerchand Pudaruth
Keyword(s):  
Resource Allocation ◽  
Network Architecture ◽  
Electrical Energy ◽  
Network Function Virtualization ◽  
Network Architectures ◽  
5G Networks ◽  
Memory Space ◽  
Network Function ◽  
5G Network ◽  
End To End

The advent of 4G and 5G broadband wireless networks brings several challenges with respect to resource allocation in the networks. In an interconnected network of wireless devices, users, and devices, all compete for scarce resources which further emphasizes the fair and efficient allocation of those resources for the proper functioning of the networks. The purpose of this study is to discover the different factors that are involved in resource allocation in 4G and 5G networks. The methodology used was an empirical study using qualitative techniques by performing literature reviews on the state of art in 4G and 5G networks, analyze their respective architectures and resource allocation mechanisms, discover parameters, criteria and provide recommendations. It was observed that resource allocation is primarily done with radio resource in 4G and 5G networks, owing to their wireless nature, and resource allocation is measured in terms of delay, fairness, packet loss ratio, spectral efficiency, and throughput. Minimal consideration is given to other resources along the end-to-end 4G and 5G network architectures. This paper defines more types of resources, such as electrical energy, processor cycles and memory space, along end-to-end architectures, whose allocation processes need to be emphasized owing to the inclusion of software defined networking and network function virtualization in 5G network architectures. Thus, more criteria, such as electrical energy usage, processor cycle, and memory to evaluate resource allocation have been proposed.  Finally, ten recommendations have been made to enhance resource allocation along the whole 5G network architecture.

scholarly journals BLOCKCHAIN-BASED NETWORK FUNCTIONS VIRTUALIZATION FOR 5G NETWORK SLICING

2021 ◽  
Vol 20 (4) ◽  
pp. 54-59
Author(s):  
Taras MAKSYMYUK ◽  
◽  
Volodymyr ANDRUSHCHAK ◽  
Stepan DUMYCH ◽  
Bohdan SHUBYN ◽  
...  
Keyword(s):  
Software Defined Radio ◽  
Network Architecture ◽  
Radio Resource Management ◽  
Mobile Network ◽  
Network Slicing ◽  
5G Network ◽  
Radio Resources ◽  
Network Functions ◽  
Mobile Network Operators

The paper proposes a new blockchain-based network architecture for 5G network functions virtualization. By using a combination of AI and blockchain technologies, proposed system provides flexible network deployment, interoperability between different mobile network operators and effective management of radio resources. Experimental testbed of the proposed system has been implemented by using cloud and edge computing infrastructure and software defined radio peripheral NI USRP 2900. Simulation results of the network slicing and radio resource management shows that proposed system is able to double the capacity of the physical network infrastructure, while ensuring the target quality of service for all users.

Future Generation Network Architecture (New Arch)

2004 ◽  
Author(s):  
David Clark ◽  
Karen Sollins ◽  
John Wroclawski ◽  
Dina Katabi ◽  
Joanna Kulik
Keyword(s):  
Network Architecture ◽  
Future Generation ◽  
Generation Network

scholarly journals On Blockchain-Based Cross-Service Communication and Resource Orchestration on Edge Clouds

Informatics ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 13
Author(s):  
Konstantinos Papadakis-Vlachopapadopoulos ◽  
Ioannis Dimolitsas ◽  
Dimitrios Dechouniotis ◽  
Eirini Eleni Tsiropoulou ◽  
Ioanna Roussaki ◽  
...  
Keyword(s):  
Network Function Virtualization ◽  
Network Resources ◽  
Service Orchestration ◽  
Network Slicing ◽  
Network Function ◽  
Resource Orchestration ◽  
Full Capacity ◽  
Cloud Datacenter ◽  
Set Up ◽  
The Internet Of Things

With the advent of 5G verticals and the Internet of Things paradigm, Edge Computing has emerged as the most dominant service delivery architecture, placing augmented computing resources in the proximity of end users. The resource orchestration of edge clouds relies on the concept of network slicing, which provides logically isolated computing and network resources. However, though there is significant progress on the automation of the resource orchestration within a single cloud or edge cloud datacenter, the orchestration of multi-domain infrastructure or multi-administrative domain is still an open challenge. Towards exploiting the network service marketplace at its full capacity, while being aligned with ETSI Network Function Virtualization architecture, this article proposes a novel Blockchain-based service orchestrator that leverages the automation capabilities of smart contracts to establish cross-service communication between network slices of different tenants. In particular, we introduce a multi-tier architecture of a Blockchain-based network marketplace, and design the lifecycle of the cross-service orchestration. For the evaluation of the proposed approach, we set up cross-service communication in an edge cloud and we demonstrate that the orchestration overhead is less than other cross-service solutions.

scholarly journals Fully Automated Cultivation of Adipose-Derived Stem Cells in the StemCellDiscovery—A Robotic Laboratory for Small-Scale, High-Throughput Cell Production Including Deep Learning-Based Confluence Estimation

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 575
Author(s):  
Jelena Ochs ◽  
Ferdinand Biermann ◽  
Tobias Piotrowski ◽  
Frederik Erkens ◽  
Bastian Nießing ◽  
...  
Keyword(s):  
Stem Cells ◽  
Deep Learning ◽  
High Throughput ◽  
High Speed ◽  
New Technologies ◽  
Human Mesenchymal Stem Cells ◽  
Simulation Software ◽  
System Capacity ◽  
Small Scale ◽  
Production Environment

Laboratory automation is a key driver in biotechnology and an enabler for powerful new technologies and applications. In particular, in the field of personalized therapies, automation in research and production is a prerequisite for achieving cost efficiency and broad availability of tailored treatments. For this reason, we present the StemCellDiscovery, a fully automated robotic laboratory for the cultivation of human mesenchymal stem cells (hMSCs) in small scale and in parallel. While the system can handle different kinds of adherent cells, here, we focus on the cultivation of adipose-derived hMSCs. The StemCellDiscovery provides an in-line visual quality control for automated confluence estimation, which is realized by combining high-speed microscopy with deep learning-based image processing. We demonstrate the feasibility of the algorithm to detect hMSCs in culture at different densities and calculate confluences based on the resulting image. Furthermore, we show that the StemCellDiscovery is capable of expanding adipose-derived hMSCs in a fully automated manner using the confluence estimation algorithm. In order to estimate the system capacity under high-throughput conditions, we modeled the production environment in a simulation software. The simulations of the production process indicate that the robotic laboratory is capable of handling more than 95 cell culture plates per day.

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