A methodology for estimating interdomain web traffic demand
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
The impact of residential broadband traffic on Japanese ISP backbones
ACM SIGCOMM Computer Communication Review
Profiling internet backbone traffic: behavior models and applications
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
The impact and implications of the growth in residential user-to-user traffic
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Analysis of a campus-wide wireless network
Wireless Networks
A first look at modern enterprise traffic
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Youtube traffic characterization: a view from the edge
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Characterizing residential broadband networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Census and survey of the visible internet
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Characterization of failures in an operational IP backbone network
IEEE/ACM Transactions on Networking (TON)
Packet-level traffic measurements from the Sprint IP backbone
IEEE Network: The Magazine of Global Internetworking
Research papers: A study of traffic from the perspective of a large pure IPv6 ISP
Computer Communications
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Tsinghua University campus network is a large campus network in China, providing volume-based and flat-rate Internet access service for more than 31,000 students and staff. In order to better understand its traffic, user behavior and pricing policies to facilitate network planning and management, we collect a one-year-long flow-based traffic log and a 10-year-long user-based log at the boundary of this campus network, and then conduct an analysis study on these two data sets. In this paper, we first present characteristics of inbound traffic flows from the aspects of traffic prediction and inference. Then we analyze the geographical origins of incoming flows, and the result reveals that USA, Japan and Korea are the most important source countries of international traffic. Our user-based investigation shows that the properties of users have important influence on their behavior, e.g., major has stronger influence on users' online time, while occupation has stronger influence on users' international traffic volume. We also find that there are more and more users choosing flat rate pricing scheme instead of volume based pricing scheme, and these users tend to over-provision when they subscribe from tiered pricing options.