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2020-02-10
Muka, Romina, Haugli, Fredrik Bakkevig, Vefsnmo, Hanne, Heegaard, Poul E..  2019.  Information Inconsistencies in Smart Distribution Grids under Different Failure Causes modelled by Stochastic Activity Networks. 2019 AEIT International Annual Conference (AEIT). :1–6.
The ongoing digitalization of the power distribution grid will improve the operational support and automation which is believed to increase the system reliability. However, in an integrated and interdependent cyber-physical system, new threats appear which must be understood and dealt with. Of particular concern, in this paper, is the causes of an inconsistent view between the physical system (here power grid) and the Information and Communication Technology (ICT) system (here Distribution Management System). In this paper we align the taxonomy used in International Electrotechnical Commission (power eng.) and International Federation for Information Processing (ICT community), define a metric for inconsistencies, and present a modelling approach using Stochastic Activity Networks to assess the consequences of inconsistencies. The feasibility of the approach is demonstrated in a simple use case.
2017-12-28
Vizarreta, P., Heegaard, P., Helvik, B., Kellerer, W., Machuca, C. M..  2017.  Characterization of failure dynamics in SDN controllers. 2017 9th International Workshop on Resilient Networks Design and Modeling (RNDM). :1–7.

With Software Defined Networking (SDN) the control plane logic of forwarding devices, switches and routers, is extracted and moved to an entity called SDN controller, which acts as a broker between the network applications and physical network infrastructure. Failures of the SDN controller inhibit the network ability to respond to new application requests and react to events coming from the physical network. Despite of the huge impact that a controller has on the network performance as a whole, a comprehensive study on its failure dynamics is still missing in the state of the art literature. The goal of this paper is to analyse, model and evaluate the impact that different controller failure modes have on its availability. A model in the formalism of Stochastic Activity Networks (SAN) is proposed and applied to a case study of a hypothetical controller based on commercial controller implementations. In case study we show how the proposed model can be used to estimate the controller steady state availability, quantify the impact of different failure modes on controller outages, as well as the effects of software ageing, and impact of software reliability growth on the transient behaviour.