Inferring link loss rates from unicast-based end-to-end measurement

In the Internet, because of huge scale and distributed administration, it is of practical importance to infer network-internal characteristics that cannot be measured directly. In this paper, based on a general framework we proposed previously, we present a feasible method of inferring packet loss rates of individual links from end-to-end measurement of uni-cast probe packets. Compared with methods using multicast probes, unicast-based inference methods are more flexible and widely applicable, whereas they have a problem with imperfect correlation in concurrent events on paths. Our method can infer link loss rates under this problem, and is applicable to various path-topologies including trees, inverse trees and their combinations. We also show simulation results which indicate potential of our unicast-based method.