Topology aware estimation methods for Internet traffic characteristics

Attempts to represent the global Internet in simulations and emulations have been difficult even at the most basic levels. The focus of our work is Internet topology and traffic matrix estimation to predict accurately Internet capacity, utilization, and congestion. We describe a forest representation of the topology of the Internet which improves on prior topologies by being more complete and accurate. We present a novel, scalable simulation environment that models the interactions of collections of flows across multi-hop networks and can accurately predict the way highly multiplexed traffic will react to congestion. We show that round trip time and ceiling not caused by congestion have a strong influence on the way traffic reacts to congestion. We show mechanisms that group large numbers of connections into units we call flocks and demonstrate that flock behavior can be seen in actual one-way delay data. Our model does not require packet-level information, but can quickly map queue depths and predict multi-hop queuing delays. Using this model, we were able to expose new phenomena that would not be apparent at lower levels of multiplexing.; The final component of this work is a traffic matrix estimation methodology that incorporates those new parameters along with the volume of traffic for each full path through the network. Ceiling and round trip time parameters were not used in earlier traffic matrix estimations because it is difficult for an Internet Service Provider to collect that data. We present a novel technique for inferring round trip times from easily gathered flow data at ISP edge nodes based on ACK ratio.