Predicting Short-Transfer Latency from TCP Arcana: A Trace-based Validation

In some contexts it may be useful to predict the latency for short TCP transfers. For example, a Web server could automatically tailor its content depending on the network path to each client, or an ``opportunistic networking'' application could improve its scheduling of data transfers.

Several techniques have been proposed to predict the latency of short TCP transfers based on online measurements of characteristics of the current TCP connection, or of recent connections from the same client. We analyze the predictive abilities of these techniques using traces from a variety of Web servers, and show that they can achieve useful accuracy in many, but not all, cases. We also show that a previously-described model for predicting short-transfer TCP latency can be improved with a simple modification. Ours is the first trace-based analysis that evaluates these prediction techniques across diverse user communities.