Abstract
A digital ICT infrastructure must be considered as a system of systems in itself, but also in interaction with other critical infrastructures such as water distributions, transportation (e.g. Intelligent Transport Systems) and Smart Power Grid control. These systems are characterised by self-organisation, autonomous sub-systems, continuous evolution, scalability and sustainability, providing both economic and social value. Services delivered involve a chain of stakeholders that share the responsibility, providing robust and secure services with stable and good performance. One crucial challenge for the different operation/control centres of the stakeholders is to manage dependability during normal operation, which may be characterised by many failures of minor consequence. In seeking to optimise the utilisation of the available resources with respect to dependability, new functionality is added with the intension to help assist in obtaining situational awareness, and for some parts enable autonomous operation. This new functionality adds complexity, such that the complexity of the (sub)systems and their operation will increase. As a consequence of adding a complex system to handle complexity, the frequency and severity of the consequences of such events may increase. Furthermore, as a side-effect of this, the preparedness will be reduced for restoration of services after a major event (that might involves several stakeholders), such as common software breakdown, security attacks, or natural disaster. This chapter addresses the dependability challenges related to the above-mentioned system changes. It is important to understand how adding complexity to handle complexity will influence the risks, both with respect to the consequences and the probabilities. In order to increase insight, a dependability modelling approach is taken, where the goal is to combine and extend the existing modelling approaches in a novel way. The objective is to quantify different strategies for management of dependability in interacting systems. Two comprehensive system examples are used to illustrate the approach. A software-defined networking example addresses the effect of moving control functionality from being distributed and embedded with the primary function, to be separated and (virtually) centralised. To demonstrate and discuss the consequences of adding more functionality both in the distributed entities serving the primary function, and centralised in the control centre, a Smart Grid system example is studied.
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Acknowledgments
This work is partly funded by Telenor–NTNU collaboration project Quality of Experience and Robustness in Telecommunications Networks, NTNU project The next generation control centres for Smart Grids (https://www.ntnu.edu/ime/smartgrids), COST Action ACROSS (IC1304) and the research lab on Quantitative modelling of dependability and performance, NTNU QUAM Lab (https://www.ntnu.edu/telematics/quam).
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Heegaard, P.E., Helvik, B.E., Nencioni, G., Wäfler, J. (2016). Managed Dependability in Interacting Systems. In: Fiondella, L., Puliafito, A. (eds) Principles of Performance and Reliability Modeling and Evaluation. Springer Series in Reliability Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-30599-8_8
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