Pirkko Kuusela

Analysis of Dependencies between Failures in the UNINETT IP Backbone Network

Dependencies between failures in operational networks may have a huge impact on their reliability and availability. In this paper we analyze failure logs to identify simultaneous and potentially correlated failures in routers and links of an IP backbone network. We show that the actual behavior of failure processes does not support the independence assumption commonly used in theoretical studies. Scatter plots are presented to visualize the failure processes, and it is seen that geographical adjacency has a pronounced effect. The existence of high correlation coefficients and high autocorrelation in some failure processes was observed. A formal analysis confirms this. The consequences of these dependencies on the provisioning of guaranteed availability are briefly discussed.

On/off process modeling of IP network failures

A reliability model for IP networks is considered, where the routers and links are modeled by independent stationary on/off processes. Component downtimes may obey any probability distribution. The model combines component reliability to a topological analysis, taking into account the routing rules of the network. This allows the derivation of on-off processes describing with high accuracy the IP-availability delivered to customers of each access router. The approach also provides estimates for risk in terms of lost traffic and allows analytic comparison of basic strategies for reliability improvement. The methodology is illustrated by studying the Finnish research backbone network.

Repairable Systems With Dependent Components: Stochastic Process Techniques and Models

We consider three approaches to the modeling of systems with repairable components by a multivariate stochastic on-off process. First, we discuss the Palm calculus framework for stationary processes and its power in the derivation of general formulae for joint downtime statistics in the case of statistically independent components. Second, a class of Generalized Semi-Markov (GSMP) models is proposed for incorporating both arbitrary component downtime distributions and statistical dependence of component failures. The case of two components is studied in detail. Third, we define the property referred to as weakened-by-failures for a system of repairable components, and prove that it implies association under fairly general conditions. We also give sufficient conditions for our GSMP models to possess this property.

Integrated platform for critical infrastructure analysis and common operating picture solutions

In this paper, we present a software framework for modeling, simulation, and analysis of critical infrastructure (CI). Our concept fuses together a state-of-the-art telecommunications and electricity distribution system simulator (CI simulator), and a Common Operating Picture visualization system (COP system). The development process included expert interviews, which were conducted to define a comprehensive set of end-user requirements from different critical infrastructure stakeholders benefitting from a common situational picture. Using the obtained results, we enhanced the CI simulator to model more precisely interdependencies in communication and electricity distribution networks in normal and abnormal situations. In addition, the simulator was extended with near future prediction capabilities using the current situation and networks’ operating conditions. The simulator also provides a real-time data stream to the COP system, whose core analysis and visualization functions were specified according to the end-user requirements collected from the interviews.