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

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.

Download Full-text

Correlating Quality of Experience and Quality of Service for Network Applications

Advances in Wireless Technologies and Telecommunication - Quality of Service Architectures for Wireless Networks ◽

10.4018/978-1-61520-680-3.ch015 ◽

2010 ◽

pp. 326-351 ◽

Cited By ~ 3

Author(s):

Mihai Ivanovici ◽

Razvan Beuran

Keyword(s):

Quality Of Service ◽

Video Transmission ◽

Quality Of Experience ◽

Point Of View ◽

File Transfer ◽

Application Performance ◽

Network Applications ◽

Network Application ◽

The One

There is a significant difference between what a network application experiences as quality at network level, and what the user perceives as quality at application level. From the network point of view, applications require certain delay, bandwidth and packet loss bounds to be met – ideally zero delay and zero loss. However, users should not be directly concerned with network conditions, and furthermore they are usually neither able to measure nor predict them. Users only expect good application performance, i.e., a fast and reliable file transfer, high quality for voice or video transmission, and so on, depending on the application being used. This is true both in wired as well as wireless networks. In order to understand network application behavior, as well as the interaction between the application and the network, one must perform a delicate task – the one of correlating the Quality of Service (QoS), i.e., the degradation induced at network level (as a measure of what the application experiences), with the Quality of Experience (QoE), i.e., the degradation perceived by the user at application level (as a measure of the user-perceived quality) (Ivanovici, 2006). This is done by simultaneously measuring the QoS degradation and the application QoE on an end-to-end basis. These measures must be then correlated by taking into account their temporal relationship. Assessing the correlation between QoE and QoS makes it possible to predict application performance given a known QoS degradation level, and to determine the QoS bounds that are required in order to attain a desired QoE level.

Download Full-text

Demand of Wireless Network and Security in Current Research

INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY ◽

10.24297/ijct.v14i6.1918 ◽

2015 ◽

Vol 14 (6) ◽

pp. 5809-5813

Author(s):

Abhishek Prabhakar ◽

Amod Tiwari ◽

Vinay Kumar Pathak

Keyword(s):

Wireless Networks ◽

Quality Of Service ◽

Wireless Network ◽

Network Performance ◽

Wireless Security ◽

Human Intervention ◽

Unauthorized Access ◽

Quality Of Service Parameters ◽

Wireless Infrastructure

Wireless security is the prevention of unauthorized access to computers using wireless networks .The trends in wireless networks over the last few years is same as growth of internet. Wireless networks have reduced the human intervention for accessing data at various sites .It is achieved by replacing wired infrastructure with wireless infrastructure. Some of the key challenges in wireless networks are Signal weakening, movement, increase data rate, minimizing size and cost, security of user and QoS (Quality of service) parameters... The goal of this paper is to minimize challenges that are in way of our understanding of wireless network and wireless network performance.

Download Full-text

Simulation and Emulation Tools for Fog Computing

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999201002152003 ◽

2020 ◽

Vol 13 ◽

Author(s):

Simar Preet Singh ◽

Rajesh Kumar ◽

Anju Sharma ◽

S. Raji Reddy ◽

Priyanka Vashisht

Keyword(s):

Quality Of Service ◽

Programming Languages ◽

Traffic Management ◽

Fog Computing ◽

Research Work ◽

Research Experience ◽

Computing Paradigm ◽

Quality Of Service Parameters ◽

User Friendly

Background: Fog computing paradigm has recently emerged and gained higher attention in present era of Internet of Things. The growth of large number of devices all around, leads to the situation of flow of packets everywhere on the Internet. To overcome this situation and to provide computations at network edge, fog computing is the need of present time that enhances traffic management and avoids critical situations of jam, congestion etc. Methods: For research purposes, there are many methods to implement the scenarios of fog computing i.e. real-time implementation, implementation using emulators, implementation using simulators etc. The present study aims to describe the various simulation and emulation tools for implementing fog computing scenarios. Results: Review shows that iFogSim is the simulator that most of the researchers use in their research work. Among emulators, EmuFog is being used at higher pace than other available emulators. This might be due to ease of implementation and user-friendly nature of these tools and language these tools are based upon. The use of such tools enhance better research experience and leads to improved quality of service parameters (like bandwidth, network, security etc.). Conclusion: There are many fog computing simulators/emulators based on many different platforms that uses different programming languages. The paper concludes that the two main simulation and emulation tools in the area of fog computing are iFogSim and EmuFog. Accessibility of these simulation/emulation tools enhance better research experience and leads to improved quality of service parameters along with the ease of their usage.

Download Full-text

ANALISIS DE CALIDAD DE SERVICIO EN REDES IPv6

Revista TECNIA ◽

10.21754/tecnia-26012016.01 ◽

2016 ◽

Vol 26 (1) ◽

pp. 7

Author(s):

Jose Carlos Tavara Carbajal

Keyword(s):

Quality Of Service ◽

Packet Loss ◽

Traffic Control ◽

Video Traffic ◽

Control Software ◽

Delay Jitter ◽

End To End Delay ◽

Analysis Of Results ◽

Ipv6 Protocol

RESUMENEste documento tiene como objetivo analizar el comportamiento de la calidad del servicio del protocolo IPv6 sobre el tráfico de video, para esto se realizó sobre un entorno real y se llevó acabo el análisis de resultados a través de un software estadístico de control del tráfico.Palabras Clave.- Calidad de Servicio, Ancho de Banda, Retardo, Fluctuación de Retardo, Pérdidas de Paquetes.ABSTRACTThis paper has aimed to analyze of the service quality of the IPv6 protocol on video traffic, this was about a real environment and was conducted analysis of results through statistical traffic control software. Key words- Quality of Service, Bandwidth, End to end delay, Jitter, Packet loss.

Download Full-text

ANALISIS DE CALIDAD DE SERVICIO EN REDES IPv6

Revista TECNIA ◽

10.21754/tecnia-250215.01 ◽

2016 ◽

Vol 26 (1) ◽

pp. 1

Author(s):

Jose Carlos Tavara Carbajal

Keyword(s):

Quality Of Service ◽

Packet Loss ◽

Traffic Control ◽

Video Traffic ◽

Control Software ◽

Delay Jitter ◽

End To End Delay ◽

Analysis Of Results ◽

Ipv6 Protocol

Este documento tiene como objetivo analizar el comportamiento de la calidad del servicio del protocolo IPv6 sobre el tráfico de video, para esto se realizó sobre un entorno real y se llevó acabo el análisis de resultados a través de un software estadístico de control del tráfico.Palabras Clave.- Calidad de Servicio, Ancho de Banda, Retardo, Fluctuación de Retardo, Pérdidas de Paquetes.ABSTRACT This paper has aimed to analyze of the service quality of the IPv6 protocol on video traffic, this was about a real environment and was conducted analysis of results through statistical traffic control software. Key words.- Quality of Service, Bandwidth, End to end delay, Jitter, Packet loss.

Download Full-text

ANALISIS DE CALIDAD DE SERVICIO EN REDES IPv6

Revista TECNIA ◽

10.21754/tecnia.v26i1.1 ◽

2016 ◽

Vol 26 (1) ◽

pp. 7

Author(s):

Jose Carlos Tavara Carbajal

Keyword(s):

Quality Of Service ◽

Packet Loss ◽

Traffic Control ◽

Video Traffic ◽

Control Software ◽

Delay Jitter ◽

End To End Delay ◽

Analysis Of Results ◽

Ipv6 Protocol

RESUMENEste documento tiene como objetivo analizar el comportamiento de la calidad del servicio del protocolo IPv6 sobre el tráfico de video, para esto se realizó sobre un entorno real y se llevó acabo el análisis de resultados a través de un software estadístico de control del tráfico.Palabras Clave.- Calidad de Servicio, Ancho de Banda, Retardo, Fluctuación de Retardo, Pérdidas de Paquetes.ABSTRACTThis paper has aimed to analyze of the service quality of the IPv6 protocol on video traffic, this was about a real environment and was conducted analysis of results through statistical traffic control software. Keywords- Quality of Service, Bandwidth, End to end delay, Jitter, Packet loss.

Download Full-text

Adaptive Reservation of Network Resources According to Video Classification Scenes

Sensors ◽

10.3390/s21061949 ◽

2021 ◽

Vol 21 (6) ◽

pp. 1949

Author(s):

Lukas Sevcik ◽

Miroslav Voznak

Keyword(s):

User Satisfaction ◽

Quality Evaluation ◽

Spatial Information ◽

Service Providers ◽

Video Quality ◽

Subjective Assessment ◽

Video Sequences ◽

Network Resources ◽

Proposed Model

Video quality evaluation needs a combined approach that includes subjective and objective metrics, testing, and monitoring of the network. This paper deals with the novel approach of mapping quality of service (QoS) to quality of experience (QoE) using QoE metrics to determine user satisfaction limits, and applying QoS tools to provide the minimum QoE expected by users. Our aim was to connect objective estimations of video quality with the subjective estimations. A comprehensive tool for the estimation of the subjective evaluation is proposed. This new idea is based on the evaluation and marking of video sequences using the sentinel flag derived from spatial information (SI) and temporal information (TI) in individual video frames. The authors of this paper created a video database for quality evaluation, and derived SI and TI from each video sequence for classifying the scenes. Video scenes from the database were evaluated by objective and subjective assessment. Based on the results, a new model for prediction of subjective quality is defined and presented in this paper. This quality is predicted using an artificial neural network based on the objective evaluation and the type of video sequences defined by qualitative parameters such as resolution, compression standard, and bitstream. Furthermore, the authors created an optimum mapping function to define the threshold for the variable bitrate setting based on the flag in the video, determining the type of scene in the proposed model. This function allows one to allocate a bitrate dynamically for a particular segment of the scene and maintains the desired quality. Our proposed model can help video service providers with the increasing the comfort of the end users. The variable bitstream ensures consistent video quality and customer satisfaction, while network resources are used effectively. The proposed model can also predict the appropriate bitrate based on the required quality of video sequences, defined using either objective or subjective assessment.

Download Full-text