Affect Corpus 2.0: An Extension of a Corpus for Actor Level Emotion Magnitude Detection

Affect Corpus 2.0: An Extension of a Corpus for Actor Level Emotion Magnitude Detection


R. Calix, G. Knapp

In Proceedings of the First ACM Multimedia Systems Conference (MMSys)
San Jose, CA, USA
February 23-25, 2011


While previous research has shown that streaming media can respond to network congestion, it is not known to what extent commercial products are responsive. Knowledge of streaming media's response to congestion encountered in the network is important in building networks that better accommodate their turbulence. This research seeks to characterize the bitrate response of Windows Streaming Media (WSM) in response to network-level metrics such as capacity, loss rate, and round-trip time. We construct a streaming media test bed that allows us to systematically vary network and content encoding characteristics to measure WSM congestion responsiveness under various streaming configurations and network conditions. We find WSM has a prominent buffering phase in which it sends data at a bitrate significantly higher than the steady-state playout rate. Overall, WSM is responsive to available capacity, but is often unfair to TCP. The additional characteristics we measure can be combined to guide emulation or simulation configurations and network traffic generators for use in further research.


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