Deriving traffic demands for operational IP networks: methodology and experience

Abstract

Engineering a large IP backbone network without an accurate, network-wide view of the tra c demands is challenging. Shifts in user behavior, changes in routing policies, and failures of network elements can result in signi cant (and sudden) uctuations in load. In this paper, we present a model of tra c demands to support tra c engineering and performance debugging of large Internet Service Provider networks. By de ning a tra c demand as a volume of load originating from an ingress link and destined to a set of egress links, we can capture and predict how routing a ects the tra c traveling between domains. To infer the tra c demands, we propose a measurement methodology that combines ow-level measurements collected at all ingress links with reachability information about all egress links. We d i scuss how to cope with situations where practical considerations limit the amount and quality of the necessary data. Speci cally, we show how to infer interdomain tra c demands using measurements collected at a smaller number of edge links | the peering links connecting to neighboring providers. We report on our experiences in deriving the tra c demands in the AT&T IP Backbone, by collecting, validating, and joining very large and diverse sets of usage, con guration, and routing data over extended periods of time. The paper concludes with a preliminary analysis of the observed dynamics of the tra c demands and a discussion of the practical implications for tra c engineering.

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