Comparative Analysis of VOIP Application with Different Queuing Schemes in WiMAX Using OPNET

Mewara, H. S.; Manghnani, Dhanwanti

doi:10.1109/cict.2015.169

Cited by 3 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Every router, whether placed in the demilitarized zone (DMZ), backbone, or endpoint area is equipped with QoS capabilities [14]. QoS is the ability to queue data traffic based on a predetermined priority of a queuing technique.…”

Section: Queuing Methodsmentioning

confidence: 99%

Comparative performance analysis of different queuing techniques for campus area network

Indrajaya,

Fauzi,

Rahman

et al. 2023

IJEECS

View full text Add to dashboard Cite

<span>A quality network infrastructure is a user demand for the increment of traffic nowadays. Due to data traffic congestion, a network’s service quality cannot fulfill the user demand, especially for streaming-type traffic. For this, an appropriate queuing method can be a convenient solution for network congestion at the time of picking traffic load. In this paper, a simulation was conducted using the OPNET application to examine the feasibility of three types of queuing methods, namely first in first out (FIFO), priority queuing (PQ), and weighted fair queuing (WFQ). During the simulation, several important parameters such as delay, throughput, and response time are considered as performance metrics and compared among four types of applications as file transfer protocol (FTP), hypertext transfer protocol (HTTP), voice over internet protocol (VoIP), and video conferencing. According to the result, it is observed that WFQ provides comparatively improved results than PQ and FIFO.</span>

show abstract

Section: Queuing Methodsmentioning

confidence: 99%

Comparative performance analysis of different queuing techniques for campus area network

Indrajaya,

Fauzi,

Rahman

et al. 2023

IJEECS

View full text Add to dashboard Cite

show abstract

“…G.729 is a low-bitrate codec designed to conserve bandwidth while maintaining acceptable voice quality. It utilizes the CS-ACELP algorithm, a form of algebraic code-excited linear prediction that efficiently compresses voice signals [3]. J Electrical Electron Eng, 2024…”

Section: Literature Reviewmentioning

confidence: 99%

“…They include FIFO, PQ, WFQ, CQ, etc. In FIFO queuing, the packet that comes first in the buffer is treated first [3] while PQ prioritizes packets based on assigned priority levels and transmits them in decreasing order of priority [7]. CQ addresses the biggest shortcoming of PQ ensuring a guaranteed minimum bandwidth to each queue, thereby protecting low-priority queues [8].…”

Section: Literature Reviewmentioning

confidence: 99%

“…It can therefore be concluded that G729 performed better than G711 in terms of delay. G711 was expected to be the better of the two since it experiences no compression [21] as compared to G729 with a compression delay of 10ms [22], which adds to the end-to-end delay. Moreover, the literature also shows that G711 requires a bandwidth of 64kbit/s, higher than that of G729 which is 8kbit/s.…”

Section: ) G729 Codec Scheme A) Packet End-to-end Delaymentioning

confidence: 99%

“…The study undertakes a performance analysis of two widely used VoIP codec schemes, G.711 and G.729, focusing on their performance characteristics under different queuing techniques within a network. G.711, a high-bitrate (64 Kbps) codec and G.729, a codec which offers a good level of call quality at a low bit rate of 8Kbps, represent two distinct approaches to voice data transmission [2,3].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Performance Analysis of G.711 and G.729 Codec Schemes under Various Queuing Techniques in Voice over Internet Protocol Transmissions

2024

J Electrical Electron Eng

View full text Add to dashboard Cite

Advancements in internet technology have enabled the integration of different traffic types i.e. data, video, and voice into a single network. This technology offers many benefits but also presents some challenges. Real-time traffic services such as VoIP require a certain Quality of Service (QoS) which cannot be guaranteed on the Internet therefore, key performance metrics become all the more important. The choice of codecs and queuing techniques becomes crucial for ensuring optimal performance, especially in networks with diverse traffic types. This research therefore compared the effects of the combinations of these tools (i.e. queuing techniques and codec schemes) on the quality of VoIP. A simulation approach using the OPNET Modeler 14.5 tool has been used to simulate a network supporting three different types of traffic namely: FTP traffic, Video conferencing traffic, and VoIP traffic. While maintaining the same topology and traffic of the network, different types of codec schemes and queuing techniques have been tested through the measurement of parameters such as delay and throughput. The custom Queuing technique showed the best performance overall while FIFO suffered the highest delay. The graphs were observed to follow the same pattern regardless of the codec scheme used however, G729 performed the better of the two as it received higher amounts of voice traffic and slightly lower delays compared to G711.

show abstract

Comparison Data Traffic Scheduling Techniques for Classifying QoS over 5G Mobile Networks

Dighriri

Alfoudi

Lee

et al. 2017

2017 31st International Conference on Advanced Information Networking and Applications Workshops (WAINA)

View full text Add to dashboard Cite

Comparative Analysis of VOIP Application with Different Queuing Schemes in WiMAX Using OPNET

Cited by 3 publications

References 8 publications

Comparative performance analysis of different queuing techniques for campus area network

Comparative performance analysis of different queuing techniques for campus area network

Performance Analysis of G.711 and G.729 Codec Schemes under Various Queuing Techniques in Voice over Internet Protocol Transmissions

Comparison Data Traffic Scheduling Techniques for Classifying QoS over 5G Mobile Networks

Contact Info

Product

Resources

About