An empirical evaluation of VoIP playout buffer dimensioning in Skype, Google talk, and MSN Messenger

Abstract

VoIP playout buffer dimensioning has long been a challenging optimization problem, as the buffer size must maintain a balance between conversational interactivity and speech quality. The conversational quality may be affected by a number of factors, some of which may change over time. Although a great deal of research effort has been expended in trying to solve the problem, how the research results are applied in practice is unclear.In this paper, we investigate the playout buffer dimensioning algorithms applied in three popular VoIP applications, namely, Skype, Google Talk, and MSN Messenger. We conduct experiments to assess how the applications adjust their playout buffer sizes. Using an objective QoE (Quality of Experience) metric, we show that Google Talk and MSN Messenger do not adjust their respective buffer sizes appropriately, while Skype does not adjust its buffer at all. In other words, they could provide better QoE to users by improving their buffer dimensioning algorithms. Moreover, none of the applications adapts its buffer size to the network loss rate, which should also be considered to ensure optimal QoE provisioning.

A spectral theory approach for extreme value analysis in a tandem of fluid queues

“…This metric is particularly relevant for interactive video with stringent delay requirements, but less so for non-interactive streaming. More recently, play-out buffer engineering regained interest in the context of Voice over IP (VoIP), with popular examples such as Skype and Google Talk [23]. Again, VoIP play-out buffer dimensioning must balance between conversational interactivity and speech quality.…”

“…Again, VoIP play-out buffer dimensioning must balance between conversational interactivity and speech quality. Proper dimensioning of the play-out buffer is known to have a decisive impact on conversation quality [23]. The real time interactive character of VoIP, however, poses again stringent restrictions on the buffer size, making the trade-off very different from non-interactive (video) streaming, which is the objective of our paper.…”

Quality of experience evaluation of voice communication: an affect-based approach

“…A good amount of research has been done in this area [17,18,[39][40][41], where QoE is estimated by modeling from the underlying QoS parameters. QoS-based methods are implicit and non-intrusive which makes them an appealing choice.…”

“…The correlation between QoS and QoE also becomes more intractable for advanced communication systems, which greatly complicates the modeling process [7]. Moreover, there are non-trivial technical details regarding its deployment in the field such as messaging overhead and traffic detection [43,44], and the buffer masking effect on the interaction between QoE and delay/loss [40].…”

Real Time Analysis of VoIP System under Pervasive Environment through Spectral Parameters

“…When voice packets do not arrive before their playout time, they are considered as lost and cannot be played when they are received. Even a single lost packet may generate audible distortion in the decoded speech signal [19,20].…”