Locating Disruptions on Internet Paths through End-to-End Measurements

In backbone networks carrying heavy traffic loads, unwanted and unusual end-to-end delay changes can happen, though possibly rarely. In order to understand and manage the network to potentially avoid such abrupt changes, it is crucial and challenging to locate where in the network lies the cause of such delays so that some corresponding actions may be taken. To tackle this challenge, the present paper proposes a simple and novel approach. The proposed approach relies only on end-to-end measurements, unlike literature approaches that often require a distributed and possibly complicated monitoring / measurement infrastructure. Here, the key idea of the proposed approach is to make use of compressed sensing theory to estimate delays on each hop between the two nodes where end-to-end delay measurement is conducted, and infer critical hops that contribute to the abrupt delay increases. To demonstrate its effectiveness, the proposed approach is applied to a real network. The results are encouraging, showing that the proposed approach is able to locate the hops that have the most significant impact on or contribute the most to abrupt increases on the end-to-end delay.