The paper deals with the problem to provide an estimation of a scenario composed by several and interdependent infrastructures. Indeed, due to the increasing presence of interdependencies, to correctly manage any infrastructure it is more and more relevant to have information about the “state” of other infrastructures, especially in critical situations. However it is unfeasible to exchange detailed data about the state of each infrastructure, due to their huge volumes and because they are considered as sensible data. To overcome such problems we propose an approach based on distributed copies of an abstract model, each attested in a given infrastructures’ control room; such models share aggregated data and operate as an Online Distributed Interdependency Estimation System. The approach is under experimental tests on a national wide electric and telecommunication networks inside the European Project MICIE.
Online Distributed Interdependency Estimation for Critical Infrastructures
Oliva G;Setola R
2011-01-01
Abstract
The paper deals with the problem to provide an estimation of a scenario composed by several and interdependent infrastructures. Indeed, due to the increasing presence of interdependencies, to correctly manage any infrastructure it is more and more relevant to have information about the “state” of other infrastructures, especially in critical situations. However it is unfeasible to exchange detailed data about the state of each infrastructure, due to their huge volumes and because they are considered as sensible data. To overcome such problems we propose an approach based on distributed copies of an abstract model, each attested in a given infrastructures’ control room; such models share aggregated data and operate as an Online Distributed Interdependency Estimation System. The approach is under experimental tests on a national wide electric and telecommunication networks inside the European Project MICIE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.