Core backbone networks must be designed to guarantee high levels of availability. Any interruption in the services that they provide may have massive consequences. For this reason there is a huge interest in developing methods able to keep the network robustness in the desired level. For the design of these methods are used models that need input information such as the operational state of network components which are stochastic variables. The aim of this paper is to provide an insight into the core networks behavior based on real operational data in order to help future related works to take more realistic assumptions. Based on failure logs provided by UNINETT we analyze availability levels and failure intensities in routers and links. We show that links may be classified in three groups with different properties. Additionally we observe that some links have similar dependability features than routers, making the perfect node assumption used on many related studies not correct. Finally, there were used parametrization techniques in order to fit the empirical processes with well-known distributions. We observe that the Weibull assumption that is traditionally used to model link failures processes fits properly the behavior of routers and short distance links but for the case of long distance fibers the gamma distribution seems to fit better.
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