Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
The changing nature of network traffic: scaling phenomena
ACM SIGCOMM Computer Communication Review
Data networks as cascades: investigating the multifractal nature of Internet WAN traffic
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
Connection-level analysis and modeling of network traffic
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
On the relationship between file sizes, transport protocols, and self-similar network traffic
ICNP '96 Proceedings of the 1996 International Conference on Network Protocols (ICNP '96)
A Behavioral Model of Web Traffic
ICNP '99 Proceedings of the Seventh Annual International Conference on Network Protocols
Scaling analysis of conservative cascades, with applications to network traffic
IEEE Transactions on Information Theory
The NLAMR network analysis infrastructure
IEEE Communications Magazine
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Over the past decade and more, several accurate but complex traffic models have been developed by just as many researchers. Among the most accurate models are those based on mathematical principles that are able to model the multifractal nature of network traffic. Unfortunately these models are hardly even usable by network engineers because they lack a connection to operational parameters that can easily be estimated based on the knowledge of the network. In this paper, we try to bridge the gap between high-level parameters describing the concerning network and the inputs the modern traffic models need to generate artificial traffic. We first build a model of the behavior of TCP over the duration of a flow, and we then approximate this behavior based on simple parameters such as for example the packet transmission time and the RTT.