Analysis and Modeling of QoS Parameters in VoIP Traffic (original) (raw)
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Simulation and modeling of packet loss on self-similar VoIP traffic
Proceedings of the 2010 …, 2010
This paper investigates the packet loss effects on the VoIP Jitter, and presents a methodology for simulating packet loss on VoIP Jitter traces with self-similar characteristics. Because of its simplicity and effectiveness, the two state Markov model or Gilbert model is used to generate packet loss patterns. We proposed a new model for self-similar VoIP traffic, this model are based on voice traffic measurements, and allowed to relate the Hurst parameter and packet loss. It is found that the relationship between Hurst parameter and packet loss obeys a power-law function with three fitted parameters. Since a number of recent studies have shown that self-similar IP traffic has negative impact on network performance, it is important to consider models that capture this behavior for the design and performance analysis of computer networks.
2011
In this paper, we analyze the jitter and packet loss behavior of Voice over Internet Protocol (VoIP) traffic by means of networks measurements and simulations results. As result of these analyses, we provide a detailed characterization and accurate modeling of these Quality of Service (QoS) parameters. Our studies have revealed that VoIP jitter can be modeled by self-similar processes with short range dependence (SRD) or long range dependence (LRD). The discovery of LRD (a kind of asymptotic fractal scaling) in VoIP jitter was followed by a further work that shows the evidence of multifractal behavior. The implication of these behaviors for VoIP and other interactive multimedia services is that receiver de-jitter buffer may not be large enough to mask the jitter with LRD and multifractal characteristics. On the other hand, we use a description of VoIP packet loss based on microscopic and macroscopic packet loss behaviors, where these behaviors can be modeled by 2-state and 4-state Markov chains, respectively. Based on the above mentioned points, we present a methodology for simulating packet loss. Besides, we found relationships between Hurst parameter (H) with the packet loss rate (PLR); these relationships are based on voice traffic measurements and can be modeled by means of a power-law function, characterized by three fitted parameters. The proposed models can be used to: (i) design a de-jitter buffer, (ii) to implement a synthetic generator of VoIP jitter data traces, where the synthetic jitter data traces can be used as test vectors to carry out the performance evaluation of a de-jitter buffer of VoIP system, and (iii) design effective schemes for packet loss recovery.
Simulation and modeling of packet loss on VoIP traffic: a power-law model
WSEAS TRANSACTIONS on …, 2009
In this paper, through an extensive analysis it is shown that VoIP traffic jitter exhibits self-similar and heavy-tail characteristics. From this analysis, we observed that α-stable distribution particularly gives the best goodness of fit; this fact has implications on the design of de-jitter buffer size. On the other hand, we investigate the packet loss effects on the VoIP jitter, and present a methodology for simulating packet loss on VoIP jitter traces. In order to represent the packet loss process, the two state Markov model or Gilbert model is used. We proposed two new models for VoIP traffic; these models are based on voice traffic measurements, and allow relating the Hurst parameter and α parameter with the packet loss rate. We found that the relationship between these parameters and packet loss rate obeys a power-law function with three fitted parameters.
Simulation and Modeling of Packet Loss on alpha-Stable VoIP Traffic
2009
In this paper, through an extensive analysis it is shown that VoIP traffic jitter exhibits heavy-tail characteristics, where α-stable distribution particularly gives the best goodness of fit; this fact has serious implications on the design of de-jitter buffer size. On the other hand, we investigate the packet loss effects on the VoIP jitter, and present a methodology for simulating packet loss on VoIP jitter traces with α-stable characteristics. In order to represent the packet loss process, the two state Markov model or Gilbert model is used. We proposed a new model for α-stable VoIP traffic, this model are based on voice traffic measurements, and allows to relate the α parameter and packet loss rate. We find that the relationship between α parameter and packet loss rate obeys a power-law function with three fitted parameters.
A Solution for Evaluating the QoS of Voice over IP
Solutions, Methods, and Applications
In this chapter, we present a solution for evaluating the Quality of Services (QoS) of Voice over Internet Protocol (VoIP). First, we present an introduction to the main concepts and mathematical background relating to QoS and Internet Protocol (IP) traffic nature, which subsequently are used in the measurements, analysis, and modeling of VoIP traffic. Secondly, we analyze network measurements and the result of the simulation in order to characterize the VoIP traffic nature. As results of this analysis, it is shown that VoIP jitter can be modeled by alpha-stable distributions and self-similar processes, with either Short or Long Range Dependence (i.e., SRD or LRD). Thirdly, we investigate the packet loss effects on the VoIP jitter, and present a methodology for simulating packet loss on VoIP jitter. Finally, we found an empirical relationship between the Hurst parameter (H) and the Packet Loss Rate (PLR); this relationship is based on voice traffic measurements and can be modeled by means of a power-law function with three fitted parameters.
WSEAS TRANSACTIONS on …, 2009
In this work, the perceived quality of VoIP communications is studied. The distributions of the number of consecutive received and lost packets, respectively named gap and burst, of a VoIP communication are modeled with discrete two-state and four-state Markov chains. Algorithms for estimating the transition probabilities between states and from these, the packet loss rate and the respective gap and burst length distributions, are described. Through a study of monitored VoIP calls, it is shown that these models can adequately represent the geometric-type decay of these distributions and that although two-state model performs well for homogeneous losses, for non-homogeneous losses the four-state model fits better. An analysis of the performance of a packet-level FEC scheme, based on-packet redundancy, is presented. The perceived packet loss rate that results of applying this correction scheme is quantified. For the studied measurements, 1-packet redundancy is sufficient to decrease the perceived loss rate below 1%. Also, the impairments of the perceived quality of voice after the FEC technique and a de-jitter buffer is quantified. The resulting equations can be used to optimize the adjust parameters of the VoIP call, e.g., level of redundancy, type of codec used and de-jitter buffer size. The proposed methodology can be extended if other types of improvements are included.
The Contributory Effect of Latency on the Quality of Voice Transmitted over the Internet
Deployment of Voice over Internet Protocol (VoIP) is rapidly growing worldwide due to the new services it provides and cost savings derived from using a converged IP network. However, voice quality is affected by bandwidth, delay, latency, jitter, packet loss e.t.c. Latency is the dominant factor that degrades quality of voice transfer. There is therefore strong need for a study on the effect of Latency with the view to improving Quality of Voice (QoV) in VoIP network. In this work, Poisson probability theorem, Markov Chain, Probability distribution theorems and Network performance metric were used to study the effect of latency on QoS in VoIP network. This is achieved by considering the effect of latency resulting from several components between two points in multiple networks. The NetQoS Latency Calculator, Net-Cracker Professional® for Modeling and Matlab/Simulink® for simulating network were tools used and the results obtained compare favourably well with theoretical facts.
Performance Evaluation of VoIP Analysis and Simulation
Journal of Engineering Research and Reports
The use of technology has impacted on communication in so many ways. The advent of voice over internet protocols (VoIP) has made the world a global village where one can reach out to any part of the universe. But a challenge exists as to how to make communication and data transmission faster, the volume of traffic, bandwidth and latency in networks, that has to be transmitted between the sender and the receiver. The overall customer experience can be improved by the use of technology, which also makes it simpler to collect client information. Data packets are addressed and routed by the Internet Protocol (IP). This research aimed at deploying jitter, throughput, network traffic delay and bandwidth (JiTTraB) as a performance metrics to measure voice over internet protocols (VoIP) to measure the Quality of Service (QoS) of networks. This method prioritizes network traffic going through a router and providing acceptable service to most users in a quest to address VoIP concerns. In comp...
Enhanced performance of packet transmission using system model over VoIP network
2010
Internet Protocol (VoIP) network is challenging. Packet loss, delay, jitter, etc. highly degrade the performance of the network. Hence more robust techniques are required to provide better level of service quality. One crucial parameter to measure service quality is packet loss. The objective of this paper is to analyze the impact of packet loss and identify proper codec techniques for VoIP traffic. We used a packet analyzer tool (wireshark) to analyze the voice traffic. We found that wireshark could serve as an effective tool for packet loss analysis. It helped us in identifying the proper codec technique that should be used for an enhanced performance in a VoIP network.
Designing a jitter buffer for QoS improvement in VoIP networks
Today main challenge in IP networks engineering is simultaneous support of different applications such as sending voice, video and data, with appropriate quality of service. The generated traffic by IP telephone, voice and video conference and on line applications, are real time and time sensitive. Jitter is an usual problem in quality of service of VoIP network. The purpose of this paper is to reduce jitter to improve quality of service. Achieve Real time voice quality is required jitter smoothing in receiver that usually is done by jitter buffer mechanism. Here we introduce an algorithm to design jitter buffer. We simulate one VoIP network by OPNeT simulator and Matlab software is used to implement the algorithm; then we compare simulation results before and after applying the algorithm and the effects of changes in buffer size on delay and jitter are checked. Output voice quality will be measured based on PESQ, according to ITU-T P.862 recommendation. The results show packet buffering reduces packets delay and makes values of them become closer together. https://sites.google.com/site/ijcsis/