Internet inter-domain traffic

By Craig Labovitz, S. Iekel-Johnson, D. McPherson, Jon Oberheide, Farnam Jahanian. Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, 2010

704 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/59cccdaef216677b5015d63850aab8ffa79e465f

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In Artificial Intelligence

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Citations in the corpus

YouTube everywhere: impact of device and infrastructure synergies on user experience (2011, background): “…Synergies on User Experience Alessandro Finamore Marco Mellia Maurizio M. Munafò Politecnico di Torino Politecnico di Torino Politecnico di Torino .namore@tlc.polito.it mellia@tlc.polito.it munafo@tlc.polito.it RubenTorres Sanjay G.Rao PurdueUniversity PurdueUniversity…”
It's not easy being green (2012, result): “(This growth rate is consistent with recent measurements [25].”
Achieving high utilization with software-driven WAN (2013, background): “Given the need for high capacity—inter-DC traffic is a significant fraction of Internet traffic and rapidly growing [20]—and unique traffic characteristics, the inter-DC WAN is often a dedicated network, distinct from the WAN that connects with ISPs to reach end users [15].”
Network characteristics of video streaming traffic (2011, background): “[21], show that video streaming contributes to 25-40% of all HTTP traffic.”
AS relationships, customer cones, and validation (2013, neutral): “The introduction of CDNs and richer peering has resulted in a flattening of the Internet topology [20, 26] where ASes avoid sending traffic via transit providers.”
A Survey of Information-Centric Networking Research (2014, background): “Moreover, recent studies on the structure of the inter-domain graph suggest that the increase of peering relationships between AS’s gradually leads to a mesh-like inter-domain graph [77], [78], therefore, employing a strictly hierarchical structure for the organization of the name space does not see”
Origami: A Convolutional Network Accelerator (2015, background): “Keywords Machine learning; pattern recognition; classification; computer vision; signal processing; accelerator; VLSI design.”