Scalable and systematic Internet-wide path and delay estimation from existing measurements

摘要

Internet-wide services and applications depend on accurate information about the internal network state to deliver good performance to end-users. However, today's Internet does not provide such information explicitly and a number of systems have been recently proposed and implemented to provide a shared measurement infrastructure for distributed applications. The goal of this work is to demonstrate that without any new measurement infrastructure or active probing we obtain composite performance estimates from AS-by-AS segments and the estimates are as good as (or even better than) those from existing estimation methodologies that use on-demand, customized active probing. The key idea behind scaling measurements to the size of the Internet is to take advantage of the known underlying structure of the network. The main contribution of this paper is an estimation algorithm that breaks down measurement data into segments, efficiently identifies relevant segments, and, by carefully stitching segments together, produces delay and path estimates between any two end points. Fittingly, we call our algorithm path stitching. Our results show remarkably good accuracy: error in delay is below 20 ms in 80% of end-to-end paths. We also show that our path stitching approach performs comparably to existing iPlane without having to instrument any new measurement node.