The authors describe a distributed network measurement infrastructure, Archipelago (Ark), which they have deployed around the world to help researchers coordinate large scale Internet measurements. The Ark infrastructure is deployed at over 31 sites around the globe and can coordinate using a tuple-based directory service. This is the primary contribution of this paper.
Ark is deployed as individual monitors (nodes) that run the Ark software. The interface is written in Ruby, though lower level access using C/C++ is supported as well. The distributed directory service support is based on Marinda, a tuple-space distributed shared memory. Monitors can modify this tuple-space to implement support for dynamic coordinate and even measurement services. The tuple-space serves as the layer of abstraction that services can use to read/write domain/range values.
As described, such an infrastructure by itself is not such a new or useful tool. However, the designers wrap the implementation with an easy to use API (in Ruby). This allows measurement studies to be written in a high level scripting language, which is conducive to rapid development and high adoption. Furthermore, the designers decided to allow access to anyone who wants it. No special authorization is needed.
Using this system, the authors have been able to gather Internet topology information that is annotated with link latencies, router ids, and AS numbers (whenever possible). This well annotated global topology can be used by many researchers for macroscopic studies. The authors claim that using Ark, they have been able to coordinate with other researchers and develop improved methods for such measurement tasks as: reconstructing router level topology, dns resolution, and ICMP & UDP topology probing.
One of the most attractive features of Ark is that it is open to anyone who wishes to gather measurement data. The paper describes the Ark infrastructure as secure, but there is not explanation of how it is secure. Indeed, if anyone can use the system, access the tuple-space shared memory to coordinate with other services/researchers, and there is no authorization, how is the system secure? This is not addressed in the paper. Some discussion of the security claim is in order.
I’d expect to see further development for Ark in the direction of built-in measurement services. It seems like the addition of a library of highly optimized (best practice) basic measurement routines would be very useful for any researcher starting out with a measurement project.
