On Measuring the Geographic Diversity of Internet Routes

Route diversity in networks is elemental for establishing reliable, high-capacity connections with appropriate security between endpoints. As for the Internet, route diversity has already been studied at both Autonomous System- and router-level topologies by means of graph theoretical disjoint paths. In this paper we complement these approaches by proposing a method for measuring the diversity of Internet paths in a geographical sense. By leveraging the recent developments in IP geolocation we show how to map the paths discovered by traceroute into geographically equivalent classes. This allows us to identify the geographical footprints of the major transmission paths between end-hosts, and building on our observations, we propose a quantitative measure for geographical diversity of Internet routes between any two hosts

Travelling Without Moving: Discovering Neighborhood Adjacencies

peer reviewedSince the early 2000's, the research community has explored many approaches to discover and study the Internet topology, designing both data collection mechanisms and models. In this paper, we introduce SAGE (Subnet AggrEgation), a new topology discovery tool that infers the hop-level graph of a target network from a single vantage point. SAGE relies on subnet-level data to build a directed acyclic graph of a network modeling how its (meshes of) routers, a.k.a. neighborhoods, are linked together. Using two groundtruth networks and measurements in the wild, we show SAGE accurately discovers links and is consistent with itself upon a change of vantage point. By mapping subnets to the discovered links, the directed acyclic graphs discovered by SAGE can be re-interpreted as bipartite graphs. Using data collected in the wild from both the PlanetLab testbed and the EdgeNet cluster, we demonstrate that such a model is a credible tool for studying computer networks