scholarly journals Data Traffic Based on Slicing in a 5G Smart Uplink System

Telecom IT ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 44-54
Author(s):  
A. Grebenshchikova ◽  
Elagin V.
Keyword(s):  
Mobile Networks ◽  
Data Transfer ◽  
Relay Node ◽  
Mobile Network ◽  
Video Stream ◽  
Base Station ◽  
Smart Devices ◽  
Future Research ◽  
Data Traffic ◽  
Fifth Generation

The paper considers the data traffic based on slicing in a 5g mobile network uplink system. Slicing is a promising technology for the fifth generation of networks that provides optimal quality of QOS services for each specific user or group of users. Data traffic that is processed by cellular networks increases every year. Therefore, we should consider all set of traffic from VoIP to M2M devices. For example, smart devices in the healthcare system transmit big data that is sensitive to latency, but also a video stream that requires minimal latency in certain cases. The paper focuses on the successful processing of traffic through a relay node, donor microstates, and a base station. All traffic is divided into three levels of QoS segmentation: sensitive, less sensitive, and low-sensitivity, using the AnyLogic simulation program. For fifth-generation 5G networks, achieving minimum latency and maximum data transfer speed within QoS is an important implementation condition. Therefore, in this paper, using simulation modeling, the main and possible results of each segment in the new generation of mobile networks are obtained. The use of a relay node in conjunction with micro-stations can ensure optimal station load and successful data processing. Also, the solutions outlined in this paper will allow you to identify a number of areas for future research to assess possible ways to design new mobile networks, or improve existing ones.

scholarly journals Towards a software-based mobility management for 5G: An experimental approach for flattened network architectures

2020 ◽  
Vol 17 (1) ◽  
pp. 51-70
Author(s):  
Jesús Calle-Cancho ◽  
José-Manuel Mendoza-Rubio ◽  
José-Luis González-Sánchez ◽  
David Cortés-Polo ◽  
Javier Carmona-Murillo
Keyword(s):  
Mobile Networks ◽  
Mobility Management ◽  
Network Performance ◽  
Mobile Network ◽  
Network Control ◽  
Network Services ◽  
Smart Devices ◽  
Network Architectures ◽  
Data Traffic ◽  
Management Capability

The number of mobile subscribers, as well as the data traffic generated by them, is increasing exponentially with the growth of wireless smart devices and the number of network services that they can support. This significant growth is pushing mobile network operators towards new solutions to improve their network performance and efficiency. Thus, the appearance of Software Defined Networking (SDN) can overcome the limitations of current deployments through decoupling the network control plane from the data plane, allowing higher flexibility and programmability to the network. In this context, the process of handling user mobility becomes an essential part of future mobile networks. Taking advantage of the benefits that SDN brings, in this article we present a novel mobility management solution. This proposal avoids the use of IP-IP tunnels and it adds the dynamic flow management capability provided by SDN. In order to analyse performance, an analytical model is developed to compare it with NB-DMM (Network-based DMM), one of the main DMM (Distributed Mobility Management) solutions. Additionally, performance is also evaluated with an experimental testbed. The results allow handover latency in real scenarios and numerical investigations to be measured, and also show that SR-DMM achieves better efficiency in terms of signaling and routing cost than NB-DMM solution.

scholarly journals Passive Method for Estimating Available Throughput for Autonomous Off-Peak Data Transfer

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Kozo Satoda ◽  
Eiji Takahashi ◽  
Takeo Onishi ◽  
Takayuki Suzuki ◽  
Daisuke Ohta ◽  
...  
Keyword(s):  
Mobile Networks ◽  
Data Transfer ◽  
Peak Load ◽  
Base Station ◽  
Base Stations ◽  
Recent Analysis ◽  
Data Traffic ◽  
End User ◽  
Lte Networks

Large demands for mobile traffic subject base stations to frequent short-term and sharp peak loads. Recent analysis of data traffic on commercial mobile networks reported that the traffic peaks can be reduced by an average of 40% without compromising the quality of experience provided to the end user, if a peak load can be shifted for at most 20 s. To reduce peak traffic, we previously proposed a method for off-peak data transfer, with which user equipment (UE) autonomously delays receiving data, and a peak load on a base station can be shifted. In terms of off-peak transfer of data, a significant problem is determining how each UE estimates available throughput. In this paper we propose a method of passively estimating available throughput of each UE. We evaluated the effectiveness of the proposed method through experiments on experimental and commercial LTE networks. The results indicate that our method obtains more than a 0.7 correlation between actual available throughput and estimated throughput.

scholarly journals Base Station Energy Efficiency Improvement for Next Generation Mobile Networks

2017 ◽  
Vol 63 (2) ◽  
pp. 187-194 ◽  
Author(s):  
Weston Mwashita ◽  
Marcel Ohanga Odhiambo
Keyword(s):  
Mobile Networks ◽  
Energy Efficient ◽  
Carbon Dioxide Emissions ◽  
Mobile Network ◽  
Base Station ◽  
Base Stations ◽  
Data Traffic ◽  
Energy Efficiency Improvement ◽  
Next Generation Mobile Networks ◽  
Operational Expenditure

Abstract As more and more Base Stations (BSs) are being deployed by mobile operators to meet the ever increasing data traffic, solutions have to be found to try and reduce BS energy consumption to make the BSs more energy efficient and to reduce the mobile networks’ operational expenditure (OPEX) and carbon dioxide emissions. In this paper, a BS sleeping technology deployable in heterogeneous networks (HetNets) is proposed. The proposed scheme is validated by using extensive OMNeT++/SimuLTE simulations. From the simulations, it is shown that some lightly loaded micro BSs can be put to sleep in a HetNet when the network traffic is very low without compromising the QoS of the mobile network.

scholarly journals Game-Theoretic Solutions for Data Offloading in Next Generation Networks

Symmetry ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 299 ◽  
Author(s):  
Muhammad Asif ◽  
Shafi Khan ◽  
Rashid Ahmad ◽  
Dhananjay Singh
Keyword(s):  
Stackelberg Game ◽  
Mobile Network ◽  
Economic Incentive ◽  
Base Station ◽  
Smart Devices ◽  
Theoretic Approach ◽  
Data Traffic ◽  
Game Theoretic ◽  
Frame Work ◽  
Internet Connections

In recent years, global mobile data traffic has seen an unprecedented increase. This is due to worldwide usage of smart devices, availability of fast internet connections, and the popularity of social media. The Mobile Network Operators (MNOs) are, therefore, facing problems in handling this huge traffic flow. Each type of traffic, including real-time video, audio, and text has its own Quality of Services (QoS) requirements which, if not met, may cause a sufficient loss of profit. Offloading of these traffics can be made more efficient so that values of QoS parameters are enhanced. In this work, we propose an incentive-based game-theoretic frame work for downloading data. The download of each type of data will get an incentive determined by the two-stage Stackelberg game. We model the communication among single Mobile Base Station (MBS) and multiple Access Points (APs) in a crowded metropolitan environment. The leader offers an economic incentive based on the traffic type and followers respond to the incentive and offload traffic accordingly. The model optimizes strategies of both the MBS and APs in order to make the best use of their utilities. For the analysis, we have used a combination of analytical and experimental methods. The numerical outcome characterized a direct process of the best possible offloading ratio and legalized the efficiency of the proposed game. Optimal incentives and optimal offloading was the achievement of our proposed game-theoretic approach. We have implemented the model in MATLAB, and the experimental results show a maximum payoff was achieved and the proposed scheme achieved Nash Equilibria.

scholarly journals Artificial intelligence techniques over the fifth generation mobile networks: a review

2021 ◽  
Vol 24 (1) ◽  
pp. 317
Author(s):  
Ashwaq N. Hassan ◽  
Sarab Al-Chlaihawi ◽  
Ahlam R. Khekan
Keyword(s):  
Artificial Intelligence ◽  
Mobile Networks ◽  
Human Error ◽  
Smart Cities ◽  
Mobile Network ◽  
Fourth Generation ◽  
Future Research ◽  
Artificial Intelligence Techniques ◽  
Fifth Generation ◽  
Sixth Generation

<span>A well Fifth generation (5G) mobile networks have been a common phrase in recent years. We have all heard this phrase and know its importance. By 2025, the number of devices based on the fifth generation of mobile networks will reach about 100 billion devices. By then, about 2.5 billion users are expected to consume more than a gigabyte of streamed data per month. 5G will play important roles in a variety of new areas, from smart homes and cars to smart cities, virtual reality and mobile augmented reality, and 4K video streaming. Bandwidth much higher than the fourth generation, more reliability and less latency are some of the features that distinguish this generation of mobile networks from previous generations.  Clearly, at first glance, these features may seem very impressive and useful to a mobile network, but these features will pose serious challenges for operators and communications companies. All of these features will lead to considerable complexity. Managing this network, preventing errors, and minimizing latency are some of the challenges that the 5th generation of mobile networks will bring. Therefore, the use of artificial intelligence and machine learning is a good way to solve these challenges. in other say, in such a situation, proper management of the 5G network must be done using powerful tools such as artificial intelligence. Various researches in this field are currently being carried out. Research that enables automated management and servicing and reduces human error as much as possible. In this paper, we will review the artificial intelligence techniques used in communications networks. Creating a robust and efficient communications network using artificial intelligence techniques is a great incentive for future research.</span><span> The importance of this issue is such that the sixth generation (6G) of cellular communications; There is a lot of emphasis on the use of artificial intelligence.</span>

scholarly journals Energy and Latency Efficient Caching in Mobile Edge Networks: Survey, Solutions, and Challenges

2021 ◽  
Author(s):  
Lubna Badri Mohammed ◽  
Alagan Anpalagan ◽  
Muhammad Jaseemuddin
Keyword(s):  
Wireless Networks ◽  
Fold Increase ◽  
Base Station ◽  
Base Stations ◽  
Smart Devices ◽  
Future Research ◽  
Data Traffic ◽  
Specific Domain ◽  
Cache Access ◽  
Edge Networks

<div><div><div><p>Future wireless networks provide research challenges with many fold increase of smart devices and the exponential growth in mobile data traffic. The advent of highly computational and real-time applications cause huge expansion in traffic volume. The emerging need to bring data closer to users and minimizing the traffic off the macrocell base station (MBS) introduces the use of caches at the edge of the networks. Storing most popular files at the edge of mobile edge networks (MENs) in user terminals (UTs) and small base stations (SBSs) caches is a promising approach to the challenges that face data-rich wireless networks. Caching at the mobile UT allows to obtain requested contents directly from its nearby UTs caches through the device-to- device (D2D) communication.</p><p>In this survey article, solutions for mobile edge computing and caching challenges in terms of energy and latency are presented. Caching in MENs and comparisons between different caching techniques in MENs are presented. An illustration of the research in cache development for wireless networks that apply intelligent and learning techniques (ILTs) in a specific domain in their design is presented. We summarize the challenges that face the design of caching system in MENs. Finally, some future research directions are discussed for the development of cache placement and cache access and delivery in MENs.</p></div></div></div>

A Power Control Strategy for IoT Sensors Developed for 5G Networks

2020 ◽  
Vol 1 (1) ◽  
pp. 22-41
Author(s):  
Weston Mwashita ◽  
Marcel Ohanga Odhiambo
Keyword(s):  
Power Control ◽  
Mobile Networks ◽  
Control Mechanism ◽  
Research Work ◽  
Mobile Network ◽  
Base Station ◽  
Open Loop ◽  
5G Networks ◽  
Fifth Generation

This research work presents a power control mechanism developed for ProSe-enabled sensors so that the sensors can be smoothly integrated into the fifth generation (5G) of mobile networks. It is strongly anticipated that 5G networks will provide an enabling environment for the 21st century innovations like the internet of things (IoT). Sensors are pivotal in IoT. The proposed power control mechanism involves an open loop power control (OLPC) mechanism that a ProSe-enabled sensor has to use to establish communication with a base station (BS) and a closed loop power control (CLPC) the BS then has use to establish transmit power levels for devices to be involved in a device to device (D2D) communication depending on the prevailing channel conditions. The results obtained demonstrate that the developed scheme does not adversely affect the quality of service (QoS) of a 5G mobile network.

scholarly journals Method for Handling Massive IoT Traffic in 5G Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3966 ◽  
Author(s):  
Safdar Marwat ◽  
Yasir Mehmood ◽  
Ahmad Khan ◽  
Salman Ahmed ◽  
Abdul Hafeez ◽  
...  
Keyword(s):  
Mobile Networks ◽  
Low Cost ◽  
Relay Node ◽  
Base Station ◽  
Data Traffic ◽  
Spectrum Utilization ◽  
Intermediate Node ◽  
Data Packets ◽  
5G Network ◽  
Iot Devices

The ever-growing Internet of Things (IoT) data traffic is one of the primary research focuses of future mobile networks. 3rd Generation Partnership Project (3GPP) standards like Long Term Evolution-Advanced (LTE-A) have been designed for broadband services. However, IoT devices are mainly based on narrowband applications. Standards like LTE-A might not provide efficient spectrum utilization when serving IoT applications. The aggregation of IoT data at an intermediate node before transmission can answer the issues of spectral efficiency. The objective of this work is to utilize the low cost 3GPP fixed, inband, layer-3 Relay Node (RN) for integrating IoT traffic into 5G network by multiplexing data packets at the RN before transmission to the Base Station (BS) in the form of large multiplexed packets. Frequency resource blocks can be shared among several devices with this method. An analytical model for this scheme, developed as an r-stage Coxian process, determines the radio resource utilization and system gain achieved. The model is validated by comparing the obtained results with simulation results.

scholarly journals Energy and Latency Efficient Caching in Mobile Edge Networks: Survey, Solutions, and Challenges

2021 ◽  
Author(s):  
Lubna Badri Mohammed ◽  
Alagan Anpalagan ◽  
Muhammad Jaseemuddin
Keyword(s):  
Wireless Networks ◽  
Fold Increase ◽  
Base Station ◽  
Base Stations ◽  
Smart Devices ◽  
Future Research ◽  
Data Traffic ◽  
Specific Domain ◽  
Cache Access ◽  
Edge Networks

<div><div><div><p>Future wireless networks provide research challenges with many fold increase of smart devices and the exponential growth in mobile data traffic. The advent of highly computational and real-time applications cause huge expansion in traffic volume. The emerging need to bring data closer to users and minimizing the traffic off the macrocell base station (MBS) introduces the use of caches at the edge of the networks. Storing most popular files at the edge of mobile edge networks (MENs) in user terminals (UTs) and small base stations (SBSs) caches is a promising approach to the challenges that face data-rich wireless networks. Caching at the mobile UT allows to obtain requested contents directly from its nearby UTs caches through the device-to- device (D2D) communication.</p><p>In this survey article, solutions for mobile edge computing and caching challenges in terms of energy and latency are presented. Caching in MENs and comparisons between different caching techniques in MENs are presented. An illustration of the research in cache development for wireless networks that apply intelligent and learning techniques (ILTs) in a specific domain in their design is presented. We summarize the challenges that face the design of caching system in MENs. Finally, some future research directions are discussed for the development of cache placement and cache access and delivery in MENs.</p></div></div></div>

scholarly journals 5G Mobile Services and Scenarios: Challenges and Solutions

2018 ◽  
Vol 10 (10) ◽  
pp. 3626 ◽  
Author(s):  
Yousaf Zikria ◽  
Sung Kim ◽  
Muhammad Afzal ◽  
Haoxiang Wang ◽  
Mubashir Rehmani
Keyword(s):  
Mobile Network ◽  
Future Internet ◽  
Autonomous Driving ◽  
Mobile Services ◽  
Data Traffic ◽  
Fifth Generation ◽  
Wide Range ◽  
Industrial Iot ◽  
5G Network ◽  
Massive Number

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.

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