Open-Source Based Prototype for Quality of Service (QoS) Monitoring and Quality of Experience (QoE) Estimation in Telecommunication Environments

2011 ◽  
Author(s):  
Bastian Huntgeburth ◽  
Michael Maruschke ◽  
Sebastian Schumann
Keyword(s):  
Quality Of Service ◽  
Open Source ◽  
Quality Of Experience ◽  
Qos Monitoring

scholarly journals ANALISIS DAN PERBANDINGAN QUALITY OF SERVICE VIDEO CONFERENCE JITSI DAN BIGBLUEBUTTON PADA VIRTUAL PRIVATE SERVER

2021 ◽  
Vol 4 (2) ◽  
pp. 192-203
Author(s):  
Ida Bagus Ary Indra Iswara ◽  
I Putu Pedro Kastika Yasa
Keyword(s):  
Quality Of Service ◽  
Open Source ◽  
Virtual Machine ◽  
Packet Loss ◽  
Video Conferencing ◽  
Video Conference ◽  
Machine Analysis ◽  
Test Scenarios

The use of video conferencing technology is increasing due to the COVID-19 pandemic. Bigbluebutton and jitsi are examples of open source video conferencing platforms that can be installed on their own servers. The server is created using a cloud-based virtual machine. Analysis of quality of service which includes delay, packet loss, throughput, and jitter is needed to determine the quality of service and the comparison of the two platforms. Observations were also made on the use of CPU, memory / RAM, and disk usage for each server. There are 3 test scenarios carried out. Each scenario is carried out on each existing VM specification. From this test, it is known that in the delay parameter, the highest bigbluebutton is obtained, which is 35,35 ms. And then the highest jitsi delay is 17,66 ms. In packet loss parameters, jitsi obtained the highest yield, namely 0,29%, while for bigbluebutton only 0,16% of packet loss was the highest. Throughput, bigbluebutton and jitsi all got very bad results. However, bigbluebutton obtained better results, namely, the highest throughput was 5.6%. While Jitsi obtained the highest throughput, namely 2,8%. Whereas for the jitter parameter, jitsi obtained 0,00 ms results on all tests in each VM. Meanwhile, bigbluebutton, get 0,1 ms on test 3 on VM 1

Quality of Experience (QoE) for Wireless Video Over Critical Communication Systems

2017 ◽  
pp. 132-167
Author(s):  
Emad Danish ◽  
Mazin I. Alshamrani
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Energy Consumption ◽  
Communication Systems ◽  
Quality Of Experience ◽  
Service Providers ◽  
Wireless Video ◽  
User Centric ◽  
Near Future

Video streaming is expected to acquire a massive share of the global internet traffic in the near future. Meanwhile, it is expected that most of the global traffic will be carried over wireless networks. This trend translates into considerable challenges for Service Providers (SP) in terms of maintaining consumers' Quality of Experience (QoE), energy consumption, utilisation of wireless resources, and profitability. However, the majority of Radio Resource Allocation (RRA) algorithms only consider enhancing Quality of Service (QoS) and network parameters. Since this approach may end up with unsatisfied customers in the future, it is essential to develop innovative RRA algorithms that adopt a user-centric approach based on users' QoE. This chapter focus on wireless video over Critical communication systems that are inspired by QoE perceived by end users. This chapter presents a background to introduce the reader to this area, followed by a review of the related up-to-date literature.

A Generic Adaptation Framework for Mobile Communication

2011 ◽  
Vol 2 (1) ◽  
pp. 46-57
Author(s):  
Hong Sun ◽  
Ning Gui ◽  
Chris Blondia
Keyword(s):  
Quality Of Service ◽  
Mobile Devices ◽  
Mobile Communication ◽  
Quality Of Experience ◽  
Adaptation Strategies ◽  
Easy Access ◽  
Mobile Terminals ◽  
System Resources ◽  
New Applications

Today, technologies are providing mobile terminals with much more powerful computational abilities. Such improvement has made it possible to run many complex applications on mobile devices. However, many of these new applications are also resource demanding. Lacking sufficient resources would cause performance failures and impact negatively on the users’ quality of experience. In order to improve this, it is important to provide the users with an easy access to specifying their requirements. It is also crucial to monitor the system resources and make corresponding adaptation immediately according to the user’s specifications. In this paper, the authors propose adaptation strategies that flexibly combine the process of monitoring and adaptation, which provides an easy way to specify user’s requirements. By tuning the quality of service, the applications’ demand on system resources is reduced, thus decreasing the chances of performance failures and improving the users’ quality of experience.

scholarly journals Customer-Oriented Quality of Service Management Method for the Future Intent-Based Networking

2020 ◽  
Vol 10 (22) ◽  
pp. 8223
Author(s):  
Mykola Beshley ◽  
Peter Veselý ◽  
Andrii Pryslupskyi ◽  
Halyna Beshley ◽  
Marian Kyryk ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Quality Management ◽  
Service Quality ◽  
Quality Of Experience ◽  
Service Management ◽  
Customer Experience ◽  
Telecommunication Networks ◽  
Service Quality Management ◽  
Management Method

The rapid development and spread of communication technologies is now becoming a global information revolution. Customers have a need for communication services, which could be flexibly configured in accordance with their Quality of Experience (QoE) requirements. Realizing the close connection between customer experience and profitability, the service provider has been placing more and more attention on customer experience and QoE. The traditional quality of service management method based on SLA (Service Level Agreement) is not sufficient as a means to provide QoE-related contracts between service providers and customers. The current SLA method is mostly limited and focused on technical aspects of QoS (Quality of Service). Furthermore, they do not follow on the network the principles and semantic approach to the QoS specification for a communication service using QoE parameters. In this paper, we propose a customer-oriented quality of service management method for future IBN (Intent-Based Networking). It is based on a new QoE metric on a scale from 1 to 5, which allows one to take into account the commercial value of e-services for customers. Based on this approach, the network configuration and functionality of network equipment automatically changes depending on customer requirements. To implement the new method of service quality management, an algorithm for routing data packets in the network was developed, taking into account the current load of the forecast path. The algorithm of billing system functioning in conditions of customer-oriented quality management in telecommunication networks has been created. To investigate the effectiveness of the proposed method of service quality management with the traditional SLA method, we developed a simulation network model with the implementation of two approaches. By conducting a simulation, it was determined that the proposed method gives an average gain of 2–5 times for the criterion of the number of customers who require high quality of experience of the service.

Quality of Service Monitoring, Diagnosis, and Adaptation for Service Level Management

2011 ◽  
pp. 41-58
Author(s):  
Guijun Wang ◽  
Changzhou Wang ◽  
Haiqin Wang ◽  
Rodolfo A. Santiago ◽  
Jingwen Jin ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Real Time ◽  
Service Level ◽  
Management Framework ◽  
Qos Management ◽  
Service Monitoring ◽  
Service Level Management ◽  
Qos Monitoring ◽  
Monitoring Service

A key requirement in Service Level Management (SLM) is managing the Quality of Services (QoS) demanded by clients and offered by providers. This managing process is complicated by the globalization and Internet scale of enterprise services and their compositions. This chapter presents two contributions to the QoS management task for SLM. First, instead of considering monitoring as an isolated service, it incorporates a monitoring service as an integral part of a comprehensive QoS management framework for SLM. Second, it includes a diagnosis service as an integral part of the QoS management framework. Using the data fed from monitoring service, diagnosis service detects system condition changes and reasons about the causes of detected degradation in networked enterprise system. With condition detection and situation understanding, the QoS management framework can then proactively activate adaptation mechanisms to maximize the system’s ability to meet QoS contract requirements of concurrent clients. Using this framework, enterprise systems can provide real time automated QoS management to optimize system resources in meeting contract requirements. This approach is validated using QoS management services integrated in a publish/subscribe style of SOA. Benefits of QoS monitoring, diagnosis, and adaptation services for responsiveness SLM are demonstrated via experiments.

scholarly journals Quality of Experience and Quality of Service Metrics for 3D Content

2018 ◽  
pp. 267-297
Author(s):  
Miguel Barreda-Ángeles ◽  
Federica Battisti ◽  
Giulia Boato ◽  
Marco Carli ◽  
Emil Dumic ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Quality Of Experience ◽  
3D Content
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