Evaluation of Multi-Gateway LoRaWAN with Different Data Traffic Models

2018 ◽  
Author(s):  
Muhammad Omer Farooq ◽  
Dirk Pesch
Keyword(s):  
Data Traffic ◽  
Traffic Models

Data Traffic Models for Broadband Backbone in 5G Networks

2021 ◽  
Author(s):  
Elena P. Ivanova ◽  
Ivelin Penkov ◽  
Teodor B. Iliev ◽  
Ivaylo S. Stoyanov
Keyword(s):  
Data Traffic ◽  
5G Networks ◽  
Traffic Models

scholarly journals QoS Management in WSN-MCN Convergence Network Using Priority Based Traffic Models

2018 ◽  
Vol 12 (3) ◽  
pp. 1159
Author(s):  
Anita Swain ◽  
Arun Kumar Ray
Keyword(s):  
Blocking Probability ◽  
Wireless Sensor ◽  
Data Traffic ◽  
Mac Layer ◽  
Preemptive Priority ◽  
M2m Communication ◽  
Traffic Models ◽  
Qos Management ◽  
Mobile Cellular ◽  
Convergence Network

Technological advancements and increased developments leads to increase the development of hand-held devices which encourage the growth of Machine-to-Machine (M2M) communication. In this context devices belongs to heterogeneous network require a common platform to meet the challenges of data centric wireless services and applications. To satisfy the needs of M2M communication, Mobile Cellular Network (MCN) and Wireless Sensor Network (WSN) converged to a single platform. In this paper two priority models has been proposed with non preemptive priority and preemptive priority to analyze the data traffic at MAC layer of the converged network. The performance matrices are determined to maintain QoS in terms of reduced dropping and blocking probability, waiting time in the queue etc. Finally, the proposed models are compared in terms of QoS factors.

5G Mobile Communication, Challenges: A Survey

2020 ◽  
Vol 2 (1) ◽  
pp. 35-42
Author(s):  
Hemalatha R ◽  
Rhesa M.J. ◽  
Revathi S
Keyword(s):  
Mobile Communication ◽  
Traffic Management ◽  
Radiation Effects ◽  
Critical Infrastructure ◽  
Security Threats ◽  
Technological Advancement ◽  
Data Traffic ◽  
Communication Challenges ◽  
5G Mobile Communication ◽  
Living Organisms

The hest for technological advancement in mobile communication is due to augmentation of wireless user. The deployment of 5G mobile communication is less than 4G mobile communication due to challenges in security like cyberwarfare, espionage, critical infrastructure threats. Nevertheless, critic of neurological discomforts, tissue damage in living organisms occur in the existence of EMF radiation. Also, physical scarcity for spectral efficiency arises due to ubiquitous data traffic. Inspite of these disputes data rate, low latency, device to device communication is also a challenge. In this paper we provide a survey on radiation effects, security threats, traffic management.

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.

scholarly journals EDCrammer: An Efficient Caching Rate-Control Algorithm for Streaming Data on Resource-Limited Edge Nodes

2019 ◽  
Vol 9 (12) ◽  
pp. 2560 ◽  
Author(s):  
Yunkon Kim ◽  
Eui-Nam Huh
Keyword(s):  
Intelligent Transportation System ◽  
Streaming Data ◽  
Data Traffic ◽  
High Quality ◽  
Data Caching ◽  
Resource Limited ◽  
Quality Video ◽  
Key Factor ◽  
Efficient Data ◽  
Art Research

This paper explores data caching as a key factor of edge computing. State-of-the-art research of data caching on edge nodes mainly considers reactive and proactive caching, and machine learning based caching, which could be a heavy task for edge nodes. However, edge nodes usually have relatively lower computing resources than cloud datacenters as those are geo-distributed from the administrator. Therefore, a caching algorithm should be lightweight for saving computing resources on edge nodes. In addition, the data caching should be agile because it has to support high-quality services on edge nodes. Accordingly, this paper proposes a lightweight, agile caching algorithm, EDCrammer (Efficient Data Crammer), which performs agile operations to control caching rate for streaming data by using the enhanced PID (Proportional-Integral-Differential) controller. Experimental results using this lightweight, agile caching algorithm show its significant value in each scenario. In four common scenarios, the desired cache utilization was reached in 1.1 s on average and then maintained within a 4–7% deviation. The cache hit ratio is about 96%, and the optimal cache capacity is around 1.5 MB. Thus, EDCrammer can help distribute the streaming data traffic to the edge nodes, mitigate the uplink load on the central cloud, and ultimately provide users with high-quality video services. We also hope that EDCrammer can improve overall service quality in 5G environment, Augmented Reality/Virtual Reality (AR/VR), Intelligent Transportation System (ITS), Internet of Things (IoT), etc.

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