Deriving traffic demands for operational IP networks: Methodology and experience

Engineering a large IP backbone network without an accurate network-wide vi ew of the traffic demands is challenging. Shifts in user behavior, changes in routing policies, and failures of network elements can result in signifi cant (and sudden) fluctuations in load. In this paper, we present a model o f traffic demands to support traffic engineering and performance debugging of large Internet Service Provider networks. By defining a traffic demand a s a volume of load originating from an ingress link and destined to a set o f egress links, we can capture and predict how routing affects the traffic traveling between domains. To infer the traffic demands, we propose a measu rement methodology that combines Bow-level measurements collected at all in gress links with reachability information about all egress links. We discus s how to cope with situations where practical considerations limit the amou nt and quality of the necessary data, Specifically, we show how to infer in terdomain traffic demands using measurements collected at a smaller number of edge links-the peering links connecting to neighboring providers. We rep ort on our experiences in deriving the traffic demands in the AT&T IP Backb one, by collecting, validating, and joining very large and diverse sets of usage, configuration, and routing data over extended periods of time. The p aper concludes with a preliminary analysis of the observed dynamics of the traffic demands and a discussion of the practical implications for traffic engineering.