Large-scale measurement and modeling of backbone Internet traffic

Abstract

There is a brewing controversy in the traffic modeling community concerning how to model backbone traffic. The fundamental work on self-similarity in data traffic appears to be contradicted by recent findings that suggest that backbone traffic is smooth. The traffic analysis work to date has focused on high-quality but limited-scope packet trace measurements; this limits its applicability to high-speed backbone traffic. This paper uses more than one year's worth of SNMP traffic data covering an entire Tier 1 ISP backbone to address the question of how backbone network traffic should be modeled. Although the limitations of SNMP measurements do not permit us to comment on the fine timescale behavior of the traffic, careful analysis of the data suggests that irrespective of the variation at fine timescales, we can construct a simple traffic model that captures key features of the observed traffic. Furthermore, the model's parameters are measurable using existing network infrastructure, making this model practical in a present-day operational network. In addition to its practicality, the model verifies basic statistical multiplexing results, and thus sheds deep insight into how smooth backbone traffic really is.