Language independent on-off voice over IP source model with lognormal transitions

The recent explosive growth of voice over IP (VoIP) solutions calls for accurate modelling of VoIP traffic. This study presents measurements of ON and OFF periods of VoIP activity from a significantly large database of VoIP call recordings consisting of native speakers speaking in some of the world's most widely spoken languages. The impact of the languages and the varying dynamics of caller interaction on the ON and OFF period statistics are assessed. It is observed that speaker interactions dominate over language dependence which makes monologue-based data unreliable for traffic modelling. The authors derive a semi-Markov model which accurately reproduces the statistics of composite dialogue measurements. © The Institution of Engineering and Technology 2013.

Deconstruction-analysis-explanation:contextualization in professional digital discourse

It is already a truism that emerging communication technologies have changed the landscape of communication in every aspect of our lives, but this is specifically true for how we communicate at work. Advances in communication technologies have enabled a wide range of digital communication modes to be utilized for both internal and external business communication; including audio and visual communication and voice-over protocols, as well as text-based channels, such as email, forums, instant messaging and social media. In spite of the wide range of available audio-visual channels, and despite the ever-increasing popularity of email, real-time text-based communication technologies (instant messaging or IM) are also on the rise (see Mak, 2014; Pazos et al., 2013; Radicati & Levenstein, 2013; and Markman in this volume). The prominence of IM is evident in the rise of this mode of communication, not only as a tool for internal business communication, but as a front-stage channel, particularly for customer service encounters or professional-client conversations (Makarem et al., 2009; Pearce et al., 2013; L. Zhang et al., 2011).

Modelling data and voice traffic over IP networks using continuous-time Markov models

Common approaches to IP-traffic modelling have featured the use of stochastic models, based on the Markov property, which can be classified into black box and white box models based on the approach used for modelling traffic. White box models, are simple to understand, transparent and have a physical meaning attributed to each of the associated parameters. To exploit this key advantage, this thesis explores the use of simple classic continuous-time Markov models based on a white box approach, to model, not only the network traffic statistics but also the source behaviour with respect to the network and application. The thesis is divided into two parts: The first part focuses on the use of simple Markov and Semi-Markov traffic models, starting from the simplest two-state model moving upwards to n-state models with Poisson and non-Poisson statistics. The thesis then introduces the convenient to use, mathematically derived, Gaussian Markov models which are used to model the measured network IP traffic statistics. As one of the most significant contributions, the thesis establishes the significance of the second-order density statistics as it reveals that, in contrast to first-order density, they carry much more unique information on traffic sources and behaviour. The thesis then exploits the use of Gaussian Markov models to model these unique features and finally shows how the use of simple classic Markov models coupled with use of second-order density statistics provides an excellent tool for capturing maximum traffic detail, which in itself is the essence of good traffic modelling. The second part of the thesis, studies the ON-OFF characteristics of VoIP traffic with reference to accurate measurements of the ON and OFF periods, made from a large multi-lingual database of over 100 hours worth of VoIP call recordings. The impact of the language, prosodic structure and speech rate of the speaker on the statistics of the ON-OFF periods is analysed and relevant conclusions are presented. Finally, an ON-OFF VoIP source model with log-normal transitions is contributed as an ideal candidate to model VoIP traffic and the results of this model are compared with those of previously published work.

Subjective quality evaluation for voice communication over MANET

Due to the dynamic and mutihop nature of the Mobile Ad-hoc Network (MANET), voice communication over MANET may encounter many challenges. We set up a subjective quality evaluation model using ITU-T E-model with extension. And through simulation in NS-2, we evaluate how the following factors impact voice quality in MANET: the number of hops, the number of route breakages, the number of communication pairs and the background traffic. Using AODV as the underlying routing protocol, and with the MAC layer changed from 802.11 DCF to 802.11e EDCF, we observe that 802.11e is more suitable for implementating voice communication over MANET. © 2005 IEEE.