A survey of 5G technologies: regulatory, standardization and industrial perspectives

Sabry

2020

IJEECS

<span>The recent advances in technology, the increased dependence on electrical energy and the emergence of the fourth industrial revolution (Industry 4.0) were all factors in the increased need for smart, efficient and reliable energy systems. This introduced the concept of the Smart Grid (SG). A SG is a potential replacement for older power grids, capable of adapting and distributing energy based on demand. SG systems are complex. They combine various components and have high requirements for real time reliable operation. This paper attempts to provide an overview of SG systems, by outlining SG architecture and various components. It also introduces communication technologies, integration and network management tools that are involved in SG systems. In addition, the paper highlights challenges and issues that need to be addressed for a successful implementation of SG. Finally, we provide suggestions for future <br /> research directions. </span>

Section: Data Transmission Technologymentioning

confidence: 99%

Smart grid in the context of industry 4.0: an overview of communications technologies and challenges

Sabry

2020

IJEECS

“…In this Special Issue, we have accepted papers in the domain of 5G Mobile Services and Scenarios. Most existing approaches for categorizing 5G services are presented from the perspective of network operators and service providers [15]. However, Yu et al [16] categorized with the aim of maximizing the satisfaction of end-users.…”

Section: A Brief Review Of Articles Of This Special Issuementioning

confidence: 99%

5G Mobile Services and Scenarios: Challenges and Solutions

et al. 2018

The Fifth generation (5G) network is projected to support large amount of data traffic and massive number of wireless connections. Different data traffic has different Quality of Service (QoS) requirements. 5G mobile network aims to address the limitations of previous cellular standards (i.e., 2G/3G/4G) and be a prospective key enabler for future Internet of Things (IoT). 5G networks support a wide range of applications such as smart home, autonomous driving, drone operations, health and mission critical applications, Industrial IoT (IIoT), and entertainment and multimedia. Based on end users’ experience, several 5G services are categorized into immersive 5G services, intelligent 5G services, omnipresent 5G services, autonomous 5G services, and public 5G services. In this paper, we present a brief overview of 5G technical scenarios. We then provide a brief overview of accepted papers in our Special Issue on 5G mobile services and scenarios. Finally, we conclude this paper.

“…HE emergence of new technologies and services has imposed substantial changes on telecommunication systems. [1][2][3]. The immediate impact of the deployment and use of these technologies arises with the need to have a telecommunications network with high capacity for data transmission.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Firefly-Genetic Algorithm for Planning of Optical Transport Networks

Oliveira

Sousa²,

Vieira³

2020

JCIS

The network design is a well-known combinatorial optimization problem that is classified as NP-Hard. The main purpose of design is often the same, to allocate and size available resources in the most possible efficient way in terms of budget, considering optimization models oriented towards minimizing costs. In this paper, it is proposed to use a hybrid optimization method called Hybrid Firefly-Genetic Algorithm to solve the Integer Linear Programming (ILP) problem, for Optical Transport Network (OTN) planning, considering cost minimization. The method combines the discrete firefly algorithm with the standard genetic algorithm. To apply this method, first it is proposed a mathematical formulation for the optical network planning problem. Two other relevant novelties of the proposed model are: 1-network modeling that considers a traffic interest matrix in which each predicted demand can be drained from its generating node (origin) to one of the possible network overflow nodes (different destination nodes); this modeling allows the dimensioning of a transport network capable of serving different service profiles at each of its nodes; 2-network resources that are efficiently allocated with determination of the capacity of each transmission system according to the best solutions for the traffic flow links. This allocation process allows the model to value those solutions with better resource sharing to the detriment of the use of several parallel links operating opportunely with idleness in each one. The results show that the proposed algorithm outperforms other metaheuristics described in the literature.