MOBILE DATA TRAFFIC ANALYSIS IN VIRTUAL PRIVATE CLOUD: A CASE-STUDY IN OPERATIONAL MOBILE NETWORK

2021 ◽  
Vol 6 (1) ◽  
pp. 49-57
Author(s):  
Ana Bogdanovska
Keyword(s):  
Mobile Network ◽  
Traffic Analysis ◽  
Data Traffic ◽  
Private Cloud ◽  
Mobile Data

Mobile Data Offloading for Streaming-Class Traffic with QoS Guarantee

2015 ◽  
Vol 7 (4) ◽  
pp. 26-42
Author(s):  
Anusree Ajith ◽  
T. G. Venkatesh
Keyword(s):  
Mobile Network ◽  
Network Capacity ◽  
Live Streaming ◽  
Data Traffic ◽  
Mobile Data ◽  
Qos Guarantee ◽  
Real Time Traffic ◽  
Video And Audio ◽  
Mobile Network Operators ◽  
Mobile Data Offloading

Faced with the tremendous increase in the amount of data traffic and associated congestion, mobile network operators are moving towards Heterogeneous networks (HetNets), in the process of expanding network capacity. Offloading data traffic onto Wi-Fi in order to avoid congestion in the backbone is an important step in the evolution of HetNets. On-the-spot and delayed offloading have been widely studied in the literature. This paper proposes an offloading algorithm which has low computational complexity. The proposed algorithm offloads data based on a balking function which is dependent on present network condition. Using extensive simulations, the authors demonstrate that the proposed algorithm achieves reduction in mean transmission delay without sacrificing much on the offloading efficiency. This technique is more efficient and applicable to real-time traffic, like live streaming video and audio, which has short and stringent delay requirements or deadlines.

Performance Evaluation of Ethernet Network for Mobile Fronthual Networks

2017 ◽  
Vol 7 (1) ◽  
pp. 287 ◽  
Author(s):  
Dawit Hadush Hailu
Keyword(s):  
Access Network ◽  
High Capacity ◽  
Mobile Network ◽  
Packet Delay ◽  
Separation Distance ◽  
Data Traffic ◽  
Link Length ◽  
Mobile Data ◽  
Radio Access ◽  
Ethernet Network

<p>Increasing mobile data traffic due to the rise of both smartphones and tablets has led to high-capacity demand of mobile data network. To meet the ever-growing capacity demand and reduce the cost of mobile network components, Cloud Radio Access Network (C-RAN) has emerged as a promising solution. In such network, the mobile operator’s Remote Radio Head (RRH) and Base Band Unit (BBU) are often separated and the connection between them has very tight timing and latency requirements imposed by Common Public Radio Interface (CPRI) and 3rd Generation Partnership Project (3GPP). This fronthaul connection is not yet provided by packet based network. To employ packet-based network for C-RAN fronthaul, the carried fronthaul traffic are needed to achieve the requirements of fronthaul streams. For this reason, the aim of this paper is focused on investigating and evaluating the feasibility of Ethernet networks for mobile fronthaul. The fronthaul requirements used to evaluate and investigate this network are maximum End to End (E2E) latency, Packet Loss Ratio (PLR) and Packet Delay Variation (PDV). The simulated results and numerical analysis confirm that the PDV and PLR of High Priority (HP) traffic in Ethernet network meet the requirements of mobile fronthaul using CPRI. However, the PDV of HP traffic meets the fronthaul network when the number of nodes in the Ethernet network is at most four. For Ethernet network, the number of nodes in the network limits the maximum separation distance between BBU and RRH (link length); for increasing the number of nodes, the link length decreases. Consequently, Radio over Ethernet (RoE) traffic should receive the priority and Quality of Service (QoS) HP can provide. On the other hand, Low Priority (LP) classes are not sensitive to QoS metrics and should be used for transporting time insensitive applications and services.</p>

A Human-in-the-Loop Architecture for Mobile Network: From the View of Large Scale Mobile Data Traffic

2017 ◽  
Vol 102 (3) ◽  
pp. 2233-2259
Author(s):  
Yuanyuan Qiao ◽  
Jianyang Yu ◽  
Wenhui Lin ◽  
Jie Yang
Keyword(s):  
Large Scale ◽  
Mobile Network ◽  
Data Traffic ◽  
Mobile Data ◽  
Human In The Loop

scholarly journals Mobility management: Deployment and adaptability aspects through mobile data traffic analysis

2016 ◽  
Vol 95 ◽  
pp. 3-14 ◽  
Author(s):  
M. Isabel Sanchez ◽  
Engin Zeydan ◽  
Antonio de la Oliva ◽  
A. Serdar Tan ◽  
Utku Yabas ◽  
...  
Keyword(s):  
Mobility Management ◽  
Traffic Analysis ◽  
Data Traffic ◽  
Mobile Data

Mobile Network Offloading

2012 ◽  
Vol 4 (3) ◽  
pp. 40-53 ◽  
Author(s):  
Michail Katsigiannis
Keyword(s):  
Energy Consumption ◽  
Access Network ◽  
Mobile Network ◽  
Local Area ◽  
Data Traffic ◽  
Mobile Data ◽  
Mobile Operator ◽  
Radio Access ◽  
Traffic Growth ◽  
Deployment Cost

The mobile data traffic growth and the high fraction of indoor-generated traffic push mobile operators to devise new deployment strategies such as mobile network offloading. The purpose of this paper is to evaluate the energy consumption and the deployment cost, based on the demanded traffic level, for a joint macro-femtocell network which enables mobile network offloading in Helsinki Metropolitan Area by 2015. This deployment is compared to an optimized only macro cellular network. The study tries to resolve under what conditions, in terms of demanded traffic, deployment cost and energy consumption, a mobile operator should deploy femtocells. Assuming that only the new network infrastructure is installed by 2015, the results show that wide-to-local area offloading is beneficial for a mobile operator to handle the mobile data traffic growth, reduce the deployment costs and the energy consumption of the radio access network.

scholarly journals An Analysis of Renewable Energy Usage by Mobile Data Network Operators

2021 ◽  
Vol 13 (4) ◽  
pp. 1886
Author(s):  
Sheraz Syed ◽  
Asad Arfeen ◽  
Riaz Uddin ◽  
Umaima Haider
Keyword(s):  
Renewable Energy ◽  
Total Energy ◽  
Carbon Emissions ◽  
Renewable Energy Sources ◽  
Mobile Network ◽  
Energy Requirements ◽  
Data Traffic ◽  
Energy Usage ◽  
Data Network ◽  
Mobile Data

The exponential growth in mobile data traffic has resulted in massive energy usage and therefore has increased the carbon footprint of the Internet. Data network operators have taken significant initiatives to mitigate the negative impacts of carbon emissions (CE). Renewable Energy Sources (RES) have emerged as the most promising way to reduce carbon emissions. This article presents the role of renewable energy (RE) in minimizing the environmental impacts of mobile data communications for achieving a greener environment. In this article, an analysis of some selected mobile data network operators’ energy consumption (EC) has been presented. Based on the current statistics of different mobile network operators, the future energy values are estimated. These estimations of carbon emissions are based on the predicted data traffic in the coming years and the percentage consumption of energy from renewable sources by the network operators. The analysis presented in this article would be helpful to develop and implement energy policies that accelerate the process of increasing the renewable shares in total energy requirements. Incrementing the share of renewable energy in total energy requirements can be a way forward to reach Goal 7 of the United Nations Sustainable Development Goals (SDGs).

Performance Comparison of Web Backend And Database: A Case Study Of Node.JS, Golang and MySQL, MongoDB

2019 ◽  
Vol 13 ◽  
Author(s):  
Faried Effendy ◽  
Taufik ◽  
Bramantyo Adhilaksono
Keyword(s):  
Response Time ◽  
Open Source ◽  
Poisson Distribution ◽  
Mobile Application ◽  
Web Applications ◽  
Performance Comparison ◽  
Memory Usage ◽  
Data Traffic ◽  
Cpu Utilization

: Substantial research has been conducted to compare web servers or to compare databases, but very limited research combines the two. Node.js and Golang (Go) are popular platforms for both web and mobile application back-ends, whereas MySQL and Go are among the best open source databases with different characters. Using MySQL and MongoDB as databases, this study aims to compare the performance of Go and Node.js as web applications back-end regarding response time, CPU utilization, and memory usage. To simulate the actual web server workload, the flow of data traffic on the server follows the Poisson distribution. The result shows that the combination of Go and MySQL is superior in CPU utilization and memory usage, while the Node.js and MySQL combination is superior in response time.

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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