Authors: David Ward, Vaida Matuziene
Addresses: JRC-Ispra, IPSC, Traceability and Vulnerability Assessment Unit, Via E. Fermi 2749, 21027 Ispra (VA), Italy. ' JRC-Ispra, IPSC, Traceability and Vulnerability Assessment Unit, Via E. Fermi 2749, 21027 Ispra (VA), Italy
Abstract: The discussion starts with the concepts of networks and sectoral infrastructures making reference to the recent Council Directive 2008-114-EC which is the basis for the identification of European critical infrastructures. Two arbitrary but interdependent infrastructures are then considered (power station and water works) which form the basis of kernel network that is then subsequently analysed under four different cases of disruption (without recovery). The kernel network therefore idealises a monolith or basic architecture consisting of just two nodes and two edges with the intent to illustrate some of the basic characteristics of the kernel as well as understand what happens in the event of a disruption and how this might propagate with consequent cascading effects. The paper begins by taking primarily a didactic and preparatory approach and then progresses into more detailed and complex modelling by illustrating the same kernel modelled using three modules by Mathworks (MATLAB, Simulink and Stateflow). Later the concepts of fuzziness and fuzzy cognitive maps are introduced and discussed in the context of network modelling. The discussion closes with possible developments of the kernel network and what tools may be exploited to model more complex situations and successfully tackle the resulting challenges.
Keywords: kernel networks; critical infrastructures; infrastructure modelling; sectoral infrastructures; EC Directive 2008-114; European Council; European Union; EU; infrastructure identification; disruption; monoliths; basic architecture; network nodes; network edges; power stations; electricity generation; water; waterworks; cascading effects; Mathworks; MATLAB; Simulink; Stateflow; fuzziness; cognitive maps; fuzzy maps; network modelling; Europe; decision sciences; risk management.
International Journal of Decision Sciences, Risk and Management, 2011 Vol.3 No.1/2, pp.98 - 128
Published online: 20 Jun 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article