EQ

Abstract

The rising popularity of data calls and the slowed global economy have posed a challenge to voice data networking—how to satisfy the growing user demand for VoIP calls under limited network resources. In a bandwidth-constrained network in particular, raising the bitrate for one call implies a lowered bitrate for another. Therefore, knowing whether it is worthwhile to raise one call's bitrate while other users might complain is crucial to the design of a user-centric rate control mechanism. To this end, previous work (Chen et al. 2012) has reported a log-like relationship between bitrate and user experience (i.e., QoE) in Skype calls. To show that the relationship extends to more general VoIP calls, we conduct a 60-participant user study via the Amazon Mechanical Turk crowdsourcing platform and reaffirm the log-like relationship between the call bitrate and user experience in widely used AMR-WB. The relationship gives rise to a simple and practical rate control scheme that exponentially quantizes the steps of rate change, therefore the name—exponential quantization (EQ). To support that EQ is effective in addressing the challenge, we show through a formal analysis that the resulting bandwidth allocation is optimal in both the overall QoE and the number of calls served. To relate EQ to existing rate control mechanisms, we show in a simulation study that the bitrates of calls administered by EQ converge over time and outperform those controlled by a (naïve) greedy mechanism and the mechanism implemented in Skype.