A hierarchical characterization of a live streaming media workload

By Eveline Veloso, Virgílio A. F. Almeida, Wagner Meira Jr, Azer Bestavros, Shudong Jin. IEEE/ACM Transactions on Networking, 2002

297 citations recorded by the source corpus.

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P2VoD: providing fault tolerant video-on-demand streaming in peer-to-peer environment (2004, background): “For example, a user will likely stop watching a VoD stream when its QoS degrades, but the user may not do the same thing for a live stream because he/she doesn’t have an option of watching it again in the future [4].”
Understanding user behavior in large-scale video-on-demand systems (2006, background): “Veloso [23] and Sripanidkulchai [21] characterized live Internet streaming media workloads.”
An analysis of live streaming workloads on the internet (2004, background): “We also .nd that recurring users often have lifetimes of at least as long as one-third of the days in the event.”
A tool for the generation of realistic network workload for emerging networking scenarios (2012, background): “…a huge amount of work exists on the characterization, modeling and simulation of network work-load (e.g., related to e-commerce platforms [7], live streaming media [8] and YouTube trafﬁc [9], peer-to-peer ﬁle sharing [10], Web [11–14] and web caching [15], malicious and unwanted trafﬁc [16–18]).”
Mesh or Multiple-Tree: A Comparative Study of Live P2P Streaming Approaches (2007, result): “55) as reported by recent empirical studies [8], [9].”
Watching television over an IP network (2008, result): “This observation is consistent with previous studies on arrival processes of live streaming servers [33,39,40].”