A study on QoS of VoIP networks: a random neural network (RNN) approach

Kapilan Radhakrishnan; Hadi Larijani

doi:10.1145/1878537.1878656

A study on QoS of VoIP networks: a random neural network (RNN) approach

Kapilan Radhakrishnan, Hadi Larijani

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Voice over Internet Protocol (VoIP) is predicted to be the replacement of the traditional PSTN telephone system. Quality of Service (QoS) of VoIP systems are more difficult to measure and implement compared to PSTN systems. The nature of QoS in VoIP networks is very variable and hence it is important to be able to measure the QoS offered by the system in real time with a low computational cost. So it is very important to measure the quality of service offered by VoIP networks. In this paper we discuss a new novel model to calculate the perceived voice quality using Random Neural Network (RNN). The RNN is an open Markovian queuing model, motivated by spiking behaviour of biological neurons that has been used for several applications. We used the feedforward architecture with different numbers of hidden neurons to test the stability of our model. We study the RNN model with 4, 5, and 6 hidden layers of neurons. Our model shows a high degree of accuracy.

Original language	English
Title of host publication	Proceedings of the 2010 Spring Simulation Multi-Conference
DOIs	https://doi.org/10.1145/1878537.1878656
Publication status	Published - 1 Jan 2010

Keywords

communications technology
random neural networks
engineering

Documents and Links

10.1145/1878537.1878656

http://researchonline.gcu.ac.uk/sec/239

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Radhakrishnan, K., & Larijani, H. (2010). A study on QoS of VoIP networks: a random neural network (RNN) approach. In Proceedings of the 2010 Spring Simulation Multi-Conference https://doi.org/10.1145/1878537.1878656

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title = "A study on QoS of VoIP networks: a random neural network (RNN) approach",

abstract = "Voice over Internet Protocol (VoIP) is predicted to be the replacement of the traditional PSTN telephone system. Quality of Service (QoS) of VoIP systems are more difficult to measure and implement compared to PSTN systems. The nature of QoS in VoIP networks is very variable and hence it is important to be able to measure the QoS offered by the system in real time with a low computational cost. So it is very important to measure the quality of service offered by VoIP networks. In this paper we discuss a new novel model to calculate the perceived voice quality using Random Neural Network (RNN). The RNN is an open Markovian queuing model, motivated by spiking behaviour of biological neurons that has been used for several applications. We used the feedforward architecture with different numbers of hidden neurons to test the stability of our model. We study the RNN model with 4, 5, and 6 hidden layers of neurons. Our model shows a high degree of accuracy.",

keywords = "communications technology, random neural networks, engineering",

author = "Kapilan Radhakrishnan and Hadi Larijani",

note = "<p>Paper presented at the 2010 Spring Simulation Multi-Conference, Orlando, Florida, 11-15 April 2010. Conference website: <a href={"}http://www.scs.org/springsim/2010{"}>http://www.scs.org/springsim/2010</a></p>",

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AU - Larijani, Hadi

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N2 - Voice over Internet Protocol (VoIP) is predicted to be the replacement of the traditional PSTN telephone system. Quality of Service (QoS) of VoIP systems are more difficult to measure and implement compared to PSTN systems. The nature of QoS in VoIP networks is very variable and hence it is important to be able to measure the QoS offered by the system in real time with a low computational cost. So it is very important to measure the quality of service offered by VoIP networks. In this paper we discuss a new novel model to calculate the perceived voice quality using Random Neural Network (RNN). The RNN is an open Markovian queuing model, motivated by spiking behaviour of biological neurons that has been used for several applications. We used the feedforward architecture with different numbers of hidden neurons to test the stability of our model. We study the RNN model with 4, 5, and 6 hidden layers of neurons. Our model shows a high degree of accuracy.

AB - Voice over Internet Protocol (VoIP) is predicted to be the replacement of the traditional PSTN telephone system. Quality of Service (QoS) of VoIP systems are more difficult to measure and implement compared to PSTN systems. The nature of QoS in VoIP networks is very variable and hence it is important to be able to measure the QoS offered by the system in real time with a low computational cost. So it is very important to measure the quality of service offered by VoIP networks. In this paper we discuss a new novel model to calculate the perceived voice quality using Random Neural Network (RNN). The RNN is an open Markovian queuing model, motivated by spiking behaviour of biological neurons that has been used for several applications. We used the feedforward architecture with different numbers of hidden neurons to test the stability of our model. We study the RNN model with 4, 5, and 6 hidden layers of neurons. Our model shows a high degree of accuracy.

KW - communications technology

KW - random neural networks

KW - engineering

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DO - 10.1145/1878537.1878656

M3 - Conference contribution

SN - 9781450300698

BT - Proceedings of the 2010 Spring Simulation Multi-Conference

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