Archipelago Monitor Statistics

Archipelago (Ark): CAIDA's active measurement infrastructure serving the network research community since 2007.
Statistical information for the topology traces taken by this individual Ark monitor is displayed below. See the main statistics page for the full list of monitors


previous
Prev monitor: waw-pl
Prev in US: tul2-us
Prev in North America: tul2-us
next
Next monitor: wlg2-nz
Next in US: xna-us
Next in North America: xna-us

wbu-us

NCAR
Boulder, CO, US (101)
IPv4 data used (switch to IPv6)

RTT quartiles versus geographical distance

Use the following link to download the data used to render this graph in ASCII, comma-separated values format here: (CSV output)

Description

This graph shows the quartiles (25th, 50th, and 75th percentiles) of round-trip times (RTTs) versus geographical distance from the probe source. The distance is calculated by looking up every hop's latitude and longitude via NetAcuity and comparing with the location of the source. The RTTs and distances are binned (to every 3 ms and 100 km, respectively) and sorted to calculate their quartile values. The straight green line represents the theoretical best RTT (given the speed of light in fiber) for a distance. The y-axis maxes out at 750ms, because of the occasional high-RTT result which skews the graph.

Motivation

By comparing RTT values with distance, we can see how much that distance dominates the speed at which packets travel. The quartile view removes the outliers that show up on the density plot and presents a cleaner view of RTT values.

Background

The round trip time for a (IP level) hop is the time (in milliseconds) that it takes for a packet to be sent from an Ark monitor to that hop and for that hop's response to be received by the monitor. Non-responding hops are ignored, and hops in a routing loop are removed.

Analysis

In general, a monitor with high-speed connectivity to the rest of the Internet will have median RTTs that rise linearly with distance. Unfortunately, for distances with only a few data points, the quartile view can give confusing results, with statistically unimportant but visually impressive ranges.