Efficient Overlay Audio Conferencing

In this paper, we present a thorough and realistic analysis of audio conferencing over application-level multicast (ALM). Through flexibility and ease-of-deployment, ALM is a compelling alternative group-communication technique to IP Multicast — which has yet to see wide-scale deployment in the Internet. However, proposed ALM techniques suffer from inherent latency inefficiencies, which we show, through realistic simulation and exploration of perceived quality in multi-party conversation, to be greatly problematic for the realisation of truly-scalable audio-conferencing systems over ALM. In this work, we propose to adapt dynamically the application-level distribution structure to the conversational pattern of the audio conference. The contribution of this paper is threefold: we develop a novel perceptual quality model for multi-party audio conversations; we provide dynamic adaptation via a simple next-speaker prediction technique and we validate the proposed approach by using a large and detailed corpus of real multi-party conversations.