AMuSe: Adaptive Multicast Services to Very Large Groups - Project Overview
Yigal Bejerano, Varun Gupta, Craig Gutterman, Gil Zussman · 2016
WiFi multicast to very large groups has gained attention as a solution for multimedia delivery in crowded areas. Yet, most recently proposed approaches do not provide performance guarantees. In this paper, we describe the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast services. AMuSe includes a lightweight feedback mechanism that allows monitoring channel quality of a large number of users. This feedback allows the system to dynamically optimize the multicast transmission rate at the AP. We implemented AMuSe on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi devices in different scenarios. We show that AMuSe supports high throughput multicast flows to hundreds of receivers while meeting quality requirements and that it outperforms other systems.