Distribution of ISP path lengths

In this section, we further examine the distribution of the end-to-end linearized distance that is accounted for by individual ISPs. We wish to understand how the effort of carrying traffic end-to-end over a wide-area path is apportioned between different ISPs. For each of the 13 nationwide ISPs in the U.S. listed in Section 3.4.1, we consider the set of paths that traverse one or more nodes in that ISP's network. For each such path, we compute the fraction of the end-to-end path that lies within the ISP's network.

Figure 13: CDF of the fraction of the end-to-end path that lies within individual ISP networks.

Figure 13 plots the CDF of this fraction for a few ISPs. In each case, we consider the paths from the U.S. university sources to the LibWeb data set. We observe that the distributions look very different. For instance, the median fraction of the end-to-end path that lies within Sprintlink is only about 0.35 whereas the corresponding fraction for UUNet is 0.75 and for Internet2 is over 0.9. Internet2 is a high-speed backbone network that connects many university campuses in the U.S. An end-to-end path that traverses Internet2 typically originates and terminates at university campuses. Therefore, the Internet2 backbone accounts for an overwhelming fraction of such end-to-end paths. UUNET accounts for a larger fraction of the paths that traverse its backbone than any other commercial ISP we considered. This may reflect the close relationship between UUNET's parent company, Worldcom (which runs the vBNS backbone [29]), and academic sites. The much smaller fraction in the case of Sprintlink is harder to explain definitively. From our conversations with people at Sprint [3,10], we have learned that academic sites are not their major customers, so Sprintlink participates minimally in carrying academic traffic. The location of our traceroute sources at academic sites may explain why Sprintlink only accounts for a small fraction of the end-to-end path. We stress, however, that the point of our analysis is not to make general claims about certain ISPs being better or worse than others. Rather it is to show that geographic analysis of end-to-end paths yields interesting insights into the role played by multiple ISPs in specific contexts (e.g., academic sites) and that these insights are consistent with our intuition.