scholarly journals Analysis and evaluation of the effectiveness of methods for ensuring the quality of service for software-defined networks of the standard 5G/IMT-2020

2021 ◽  
Vol 9 (5) ◽  
pp. 14-25
Author(s):  
Behrooz Daneshmand
Keyword(s):  
Quality Of Service ◽  
Open Source ◽  
Large Network ◽  
Network Resources ◽  
Machine Type ◽  
Machine Type Communications ◽  
5G Network ◽  
Definition Of ◽  
High Level

The quality of service (QoS) in networking is the process of managing network resources to reduce packet loss and to lower network jitter and latency. QoS has been widely used in traditional network and can also be implemented in the 5G standard based on a software-defined network (SDN). A traditional network carries several challenges, such as vendor dependency, the complexity of managing a large network, dynamically changing forwarding policies, and more. Software-defined networking is a new networking strategy designed to address the challenges of a traditional IP network, such as high levels of complexity and inability to adapt to the new quality of service requirements in a timely manner. The fundamental idea behind SDNs compared to the conventional networking paradigm is the creation of horizontally integrated systems through the separation of the control and the data plane while providing an increasingly sophisticated set of abstractions. Recently, various SDN-enabled QoS frameworks have emerged that offer many possibilities for network reconfiguration and high-level definition of policies. QoS requirements for 5G networks have been defined on the basis of three main categories of use cases: extreme mobile broadband (xMBB), massive machine type communications (mMTC) IoT/M2M devices, and highly reliable М2М-communication (ultra-reliable machine-type communications – uMTC). This paper analyzes and surveys the QoS based on the openflow protocol method and QoS based on open-source SDN controllers method in 5G network. In addition, we discuss various architectural issues of open-source SDN controllers network and examine their impact on the QoS. Furthermore, we outline the characteristics of the QoS parameters such as latency, availability, reliability, jitter, and bandwidth in the 5G network. Finally, the article discusses and compares parameters of the QoS in 5G determined by world’s leaders in 5G technology.

Effect of Heterogeneous Traffic on Quality of Service in 5G Network

2019 ◽  
pp. 469-478
Author(s):  
Omar Abdulkareem Mahmood ◽  
Abdukodir Khakimov ◽  
Ammar Muthanna ◽  
Alexander Paramonov
Keyword(s):  
Quality Of Service ◽  
Heterogeneous Traffic ◽  
5G Network

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

scholarly journals Quality of Service to the Regional Road Transport Service

2016 ◽  
Vol 1 (2) ◽  
pp. 216
Author(s):  
Suela E.Shpuza
Keyword(s):  
Quality Of Service ◽  
Customer Service ◽  
Performance Standards ◽  
Road Transport ◽  
Service Organizations ◽  
Transport Service ◽  
Lack Of Information ◽  
And Performance ◽  
High Level

Performance is measured and done, the quality represents a key element to achieve the performance, especially customer service quality. In response to the pressure of globalization, the market increasingly competitive and volatile market dynamics that, many organizations actively seeking ways to add value to their services and improve their quality of service. Organizations usually tend to make their operations efficient priority. This process begins with the assessment of nevojave customers, their requirements and assessing the performance of domestic human resources in organization and performance depends on the outcome of the estimated earlier. Since this process can proceed in different directions. The causes of these results may be the lack of information and support of high-level management, performance standards unclear, inaccuracies assessors, very large number of forms to be completed and the use of software for the opposite purpose.

scholarly journals IMPACT OF QUEUING DISCIPLINES ON THE PERFORMANCE OF MULTI-CLASS TRAFFIC IN A NETWORK

2021 ◽  
Vol 9 (1) ◽  
pp. 691-697
Author(s):  
N. Sugirtham, R. Sherine Jenny
Keyword(s):  
Quality Of Service ◽  
User Satisfaction ◽  
File Transfer ◽  
Network Resources ◽  
Network Applications ◽  
End To End Delay ◽  
Opinion Score ◽  
Quality Of Service Parameters ◽  
First In First Out

Network applications demand quality of service for enhanced call quality and increased user satisfaction. Hence, implementing queuing discipline at switches and routers in a network will govern the way packets are buffered while waiting for transmission. Queuing disciplines like first-in first-out (FIFO) queuing, priority queuing (PQ), weighted-fair queuing (WFQ), custom queuing and modified weighted round robin are more prominently deployed in network applications. These queuing disciplines help to control and manage network resources by fixing priorities for specific types of data on the network. The paper aims to analyze the quality of service parameters for various real time applications like File transfer protocol(FTP), email, database, Voice over IP(VOIP), video and web browsing,etc., and helps to optimise the use of available network resources. Moreover the quality of the network is compared using different QoS parameters such as end-to-end delay, throughput, jitter and Mean Opinion Score (MOS). This paper focuses on various queuing disciplines with low and high network traffic.

FOCUS ON COORDINATION OF OPERATORS ENSURING THE QUALITY OF SERVICE IN TOURISM

2020 ◽  
Author(s):  
Mincho Polimenov ◽  
Keyword(s):  
Quality Of Service ◽  
Production Process ◽  
Level Of Service ◽  
Production Cycle ◽  
Work Processes ◽  
Organization And Management ◽  
Culture Of Consumption ◽  
High Level ◽  
Tourist Service

The report focuses on the quality of service in tourism and in particular on the quality of blanks and work processes in the various issuing units and their coordination in the overall production process. Investments are focused not only on improved innovations in machine software and equipment, but also on such tricks and connections in the production cycle providing a high level of service and culture of consumption. Facilitating the processes provides a level of competition and creates an opportunity for affordability in quality and price. Emphasis is placed on the flexibility of tour operators and the tourist product and tourist service they offer, their quality, organization and management. Satisfying the modern "global tourist" requires not only knowledge of the structure of the offered tourist product and service, but also seeks an answer to the question "How" to be created and implemented.

A Mechanism for Securing Hybrid Cloud Outsourced Data

2015 ◽  
pp. 73-83 ◽  
Author(s):  
Abdullah El-Haj ◽  
Shadi Aljawarneh
Keyword(s):  
Quality Of Service ◽  
Communication Networks ◽  
Security Policy ◽  
Detection System ◽  
Network Access ◽  
Network Resources ◽  
Outsourced Data ◽  
Secure Data Transmission ◽  
Cloud Network

The existing research related to security mechanisms only focuses on securing the flow of information in the communication networks. There is a lack of work on improving the performance of networks to meet quality of service (QoS) constrains for various services. The security mechanisms work by encryption and decryption of the information, but do not consider the optimised use of the network resources. In this paper the authors propose a Secure Data Transmission Mechanism (SDTM) with Preemption Algorithm that combines between security and quality of service. Their developed SDTM enhanced with Malicious Packets Detection System (MPDS) which is a set of technologies and solutions. It enforces security policy and bandwidth compliance on all devices seeking to access Cloud network computing resources, in order to limit damage from emerging security threats and to allow network access only to compliant and trusted endpoint devices.

Pricing Quality of Service in Diffserv IP Networks

2010 ◽  
pp. 1245-1251 ◽  
Author(s):  
Vladanka S. Acimovic-Raspopovic ◽  
Mirjana D. Stojanovic
Keyword(s):  
Quality Of Service ◽  
Network Resources ◽  
Telecommunication Services ◽  
Ip Qos ◽  
Qos Differentiation ◽  
Commercial Networks ◽  
Standard Application ◽  
Voice Data ◽  
Pricing Schemes

In order to reduce costs and make it easier to integrate disparate systems, networked and virtual organizations (NVOs) should adopt open technology standards throughout the entire organization—standard computing architectures, standard networks, and standard application interfaces. The Internet protocol (IP) technology has been foreseen as a basic networking infrastructure that supports communication requirements of NVOs. With the growing demand for the integration of heterogeneous telecommunication services (e.g., voice, data, video and multimedia), there is a strong need for deploying quality of service (QoS) in IP-based networks. Under such circumstances, the flat pricing models that have been satisfying in traditional best-effort Internet so far do not encourage users to make reasonable use of resources. QoS differentiation introduces a clear need for incentives to be offered to users to encourage them to choose the service that is most appropriate for their needs. In commercial networks, this can be most effectively achieved through pricing. Falkner, Devetsikiotis, and Lambadaris (2000) and Da Silva (2000) supplied comprehensive reviews and evaluation of pricing schemes developed during the nineties and mainly related with per-flow IP QoS approaches, such as the integrated services (IntServ) specified by Braden, Clark, and Shenker (1994). Proliferation of the differentiated services framework, since the late 90s posed a number of new issues and resulted in novel proposals for pricing IP QoS and network resources.

scholarly journals KLASIFIKASI PENGGUNAAN PROTOKOL KOMUNIKASI PADA TRAFIK JARINGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR

2016 ◽  
Vol 16 (1) ◽  
pp. 67
Author(s):  
Komang Kompyang Agus Subrata ◽  
I Made Oka Widyantara ◽  
Linawati Linawati
Keyword(s):  
Quality Of Service ◽  
Network Traffic ◽  
Network Architecture ◽  
Nearest Neighbor ◽  
Computer Network ◽  
Data Communication ◽  
Data Capture ◽  
K Nearest Neighbor ◽  
High Level

ABSTRACT—Network traffic internet is data communication in a network characterized by a set of statistical flow with the application of a structured pattern. Structured pattern in question is the information from the packet header data. Proper classification to an Internet traffic is very important to do, especially in terms of the design of the network architecture, network management and network security. The analysis of computer network traffic is one way to know the use of the computer network communication protocol, so it can be the basis for determining the priority of Quality of Service (QoS). QoS is the basis for giving priority to analyzing the network traffic data. In this study the classification of the data capture network traffic that though the use of K-Neaerest Neighbor algorithm (K-NN). Tools used to capture network traffic that wireshark application. From the observation of the dataset and the network traffic through the calculation process using K-NN algorithm obtained a result that the value generated by the K-NN classification has a very high level of accuracy. This is evidenced by the results of calculations which reached 99.14%, ie by calculating k = 3. Intisari—Trafik jaringan internet adalah lalu lintas ko­mu­nikasi data dalam jaringan yang ditandai dengan satu set ali­ran statistik dengan penerapan pola terstruktur. Pola ter­struktur yang dimaksud adalah informasi dari header paket data. Klasifikasi yang tepat terhadap sebuah trafik internet sa­ngat penting dilakukan terutama dalam hal disain perancangan arsitektur jaringan, manajemen jaringan dan keamanan jari­ngan. Analisa terhadap suatu trafik jaringan komputer meru­pakan salah satu cara mengetahui penggunaan protokol komu­nikasi jaringan komputer, sehingga dapat menjadi dasar pe­nen­tuan prioritas Quality of Service (QoS). Dasar pemberian prio­ritas QoS adalah dengan penganalisaan terhadap data trafik jaringan. Pada penelitian ini melakukan klasifikasi ter­hadap data capture trafik jaringan yang di olah menggunakan Algoritma K-Neaerest Neighbor (K-NN). Apli­kasi yang digu­nakan untuk capture trafik jaringan yaitu aplikasi wireshark. Hasil observasi terhadap dataset trafik jaringan dan melalui proses perhitungan menggunakan Algoritma K-NN didapatkan sebuah hasil bahwa nilai yang dihasilkan oleh klasifikasi K-NN memiliki tingkat keakuratan yang sangat tinggi. Hal ini dibuktikan dengan hasil perhi­tungan yang mencapai nilai 99,14 % yaitu dengan perhitungan k = 3. DOI: 10.24843/MITE.1601.10

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