Dhamdhere, a researcher at CAIDA, said the Archipelago infrastructure has collected 6 terabytes of compressed data since 2007, all of which is available to network research and operators. CAIDA provides the raw traceroutes in their original form, curated topology data sets and asynchronous number topologies for IPv4 and IPv6.
“One of the goals of a currently funded project that we’re working on is to make it easier for researchers and people interested in this kind of analysis to actually access this data and do interesting things with it,” Dhamdhere said. “We’re building support for rich queries on this traceroute data, and the idea is to put them together with other kinds of data such as geolocation, annotated AS-level topologies, and router-level topologies.”
Eventually, CAIDA wants to provide data that can be used for regional analysis such as measuring how many routes for Canada-to-Canada communications exited Canada and traverse through US networking hubs.
“Suppose we predicted that a certain region was going to be affected in the sense of a natural disaster like a hurricane or a storm coming up or political instability. We’d like to know all the paths from our current monitors that actually traverse that region,” Dhamdhere said. “These paths might be rerouted or might even go down when something actually happens.”
He said CAIDA is looking for volunteers to host additional Archipelago monitors, which are Raspberry Pi computers that cost only $35 each. People with Archipelago monitors can take advantage of an interactive topology-on-demand service called Vela, which visualizes traceroutes on a map. Another CAIDA service is a DNS-based geolocation service, which gives hints about the geographic location of a domain. Finally, CAIDA offers a repository of tools and data regarding autonomous systems (AS), including a map that uses geolocation data to infer where an AS has deployed infrastructure.
“We have an interface where operators can go in and enter corrections to the inferences we’ve made,” Dhamdhere added.
One work in progress at CAIDA is data about which networks peer at IXPs.
See IETF panel reported in ISOC https://www.internetsociety.org/publications/ietf-journal-november-2014/experts-say-economics-and-politics-hamper-efficient-routing-internet-data
Dhamdhere, a researcher at CAIDA, said the Archipelago infrastructure has collected 6 terabytes of compressed data since 2007, all of which is available to network research and operators. CAIDA provides the raw traceroutes in their original form, curated topology data sets and asynchronous number topologies for IPv4 and IPv6.
“One of the goals of a currently funded project that we’re working on is to make it easier for researchers and people interested in this kind of analysis to actually access this data and do interesting things with it,” Dhamdhere said. “We’re building support for rich queries on this traceroute data, and the idea is to put them together with other kinds of data such as geolocation, annotated AS-level topologies, and router-level topologies.”
Eventually, CAIDA wants to provide data that can be used for regional analysis such as measuring how many routes for Canada-to-Canada communications exited Canada and traverse through US networking hubs.
“Suppose we predicted that a certain region was going to be affected in the sense of a natural disaster like a hurricane or a storm coming up or political instability. We’d like to know all the paths from our current monitors that actually traverse that region,” Dhamdhere said. “These paths might be rerouted or might even go down when something actually happens.”
He said CAIDA is looking for volunteers to host additional Archipelago monitors, which are Raspberry Pi computers that cost only $35 each. People with Archipelago monitors can take advantage of an interactive topology-on-demand service called Vela, which visualizes traceroutes on a map. Another CAIDA service is a DNS-based geolocation service, which gives hints about the geographic location of a domain. Finally, CAIDA offers a repository of tools and data regarding autonomous systems (AS), including a map that uses geolocation data to infer where an AS has deployed infrastructure.
“We have an interface where operators can go in and enter corrections to the inferences we’ve made,” Dhamdhere added.
One work in progress at CAIDA is data about which networks peer at IXPs.