Real-time comparison of quality of interfaces (QoI) by mobile devices over heterogeneous radio networks

2004 ◽  
Author(s):  
E. van den Berg ◽  
S. Madhani ◽  
Tao Zhang
Keyword(s):  
Real Time ◽  
Mobile Devices ◽  
Radio Networks

scholarly journals Effective Bandwidth Prediction through Statistical Technique over Heterogeneous Networks

2019 ◽  
Vol 8 (12) ◽  
pp. 508-512
Keyword(s):  
Real Time ◽  
Mobile Devices ◽  
Video Streaming ◽  
Heterogeneous Networks ◽  
Streaming Media ◽  
Statistical Technique ◽  
Prediction Algorithm ◽  
Effective Bandwidth ◽  
Battery Life

Real time Streaming Media (Video Streaming) applications are mostly popular on the mobiles and computers using Internet. Due to higher demand of video streaming through wireless network and mobile devices, video are being transmitted through various heterogeneous networks so as to efficiently deliver to the clients devices. This has resulted in the lower quality of real time video, since real time streaming media has quality of parameter requirements like high bandwidth, low packet loss ratio, higher delay and jitter. Streaming media such as video through heterogeneous networks has more challenges due to unreliable wireless networks and device mobility; moreover bandwidth, delay and loss are unknown in advance and are unbounded. In this paper, effective bandwidth prediction through statistical technique over heterogeneous wireless communication networks is proposed. Statistical technique offers computationally efficient bandwidth prediction with reasonably better accuracy. Especially with mobile devices with limited computational power and battery life, necessitates better bandwidth prediction with efficient but computationally simpler algorithms. Bandwidth predictions assist in selecting effective network for video streaming when various heterogeneous networks are available. Detailed bandwidth prediction algorithm is presented with use of quality of service (QoS) parameters data sets available online.

Development and Application of Quality Control System for Highway Subgrade Construction

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Tong Wang
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Detection Method ◽  
System Development ◽  
Effective Control ◽  
Construction Process ◽  
Development Mode ◽  
The Road ◽  
Whole Process

The compaction quality of the subgrade is directly related to the service life of the road. Effective control of the subgrade construction process is the key to ensuring the compaction quality of the subgrade. Therefore, real-time, comprehensive, rapid and accurate prediction of construction compaction quality through informatization detection method is an important guarantee for speeding up construction progress and ensuring subgrade compaction quality. Based on the function of the system, this paper puts forward the principle of system development and the development mode used in system development, and displays the development system in real-time to achieve the whole process control of subgrade construction quality.

CONTROL IN REAL TIME THE DENSITY OF PRODUCT AT VARIOUS STAGES OF THE TECHNOLOGICAL PROCESS OF SUGAR PRODUCTION

2020 ◽  
Author(s):  
S.B. Kudryashev ◽  
◽  
N.S. Assev ◽  
R.D. Belashov ◽  
V.A. Naumenko ◽  
...  
Keyword(s):  
Real Time ◽  
Technological Process ◽  
Sugar Industry ◽  
Sugar Production ◽  
Production Processes ◽  
Quality Of Products

The article is devoted to solving one of the most important problems of the development of the sugar industry in Russia – the modernization of sugar production processes. Today, sugar production is actively being modernized, shifting most of its processes to the path of avomatization and optimization to improve the quality of products. This article describes one of the main ways to obtain information about the concentration of sucrose in syrup in the production of sugar.

What's my App?

2021 ◽  
Vol 48 (4) ◽  
pp. 41-44
Author(s):  
Dena Markudova ◽  
Martino Trevisan ◽  
Paolo Garza ◽  
Michela Meo ◽  
Maurizio M. Munafo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Natural Language Processing ◽  
Real Time ◽  
Language Processing ◽  
Traffic Management ◽  
Quality Of Experience ◽  
Broadband Internet ◽  
Management Policies ◽  
Control Traffic

With the spread of broadband Internet, Real-Time Communication (RTC) platforms have become increasingly popular and have transformed the way people communicate. Thus, it is fundamental that the network adopts traffic management policies that ensure appropriate Quality of Experience to users of RTC applications. A key step for this is the identification of the applications behind RTC traffic, which in turn allows to allocate adequate resources and make decisions based on the specific application's requirements. In this paper, we introduce a machine learning-based system for identifying the traffic of RTC applications. It builds on the domains contacted before starting a call and leverages techniques from Natural Language Processing (NLP) to build meaningful features. Our system works in real-time and is robust to the peculiarities of the RTP implementations of different applications, since it uses only control traffic. Experimental results show that our approach classifies 5 well-known meeting applications with an F1 score of 0.89.

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