WiFi networks have been globally deployed and most mobile devices are currently WiFi-enabled. While WiFi has been proposed for multimedia content distribution, its lack of adequate support for multicast services hinders its ability to provide multimedia content distribution to a large number of devices. In this paper, we present the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast services. AMuSe is based on accurate receiver feedback and incurs a small control overhead. In particular, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes, which periodically send information about the channel quality to the multicast sender. This feedback information can be used by the multicast sender to optimize multicast service quality, e.g., by dynamically adjusting transmission bitrate. AMuSe does not require any changes to the standards or any modifications to the WiFi devices.  We implemented AMuSe on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi devices , both with and without interference sources. Our extensive experiments demonstrate that AMuSe can provide accurate feedback in a dense multicast environment. It outperforms several alternatives even in the case of external interference and changing network conditions.
['Varun Gupta', 'Yigal Bejerano', 'Craig Gutterman', 'Jaime Ferragut', 'Katherine Guo', 'Thyaga Nandagopal', 'Gil Zussman']
Light-Weight Feedback Mechanism for WiFi Multicast to Very Large Groups—Experimental Evaluation