The paradigm of complexity is pervading both science and engineering, le- ing to the emergence of vel approaches oriented at the development of a systemic view of the phemena under study; the de?nition of powerful tools for modelling, estimation, and control; and the cross-fertilization of di?erent disciplines and approaches. One of the most promising paradigms to cope with complexity is that of networked systems. Complex, dynamical networks are powerful tools to model, estimate, and control many interesting phemena, like agent coordination, synch- nization, social and ecomics events, networks of critical infrastructures, resourcesallocation,informationprocessing,controlovercommunicationn- works, etc. Advances in this ?eld are highlighting approaches that are more and more oftenbasedondynamicalandtime-varyingnetworks,i.e.networksconsisting of dynamical des with links that can change over time. Moreover, recent techlogical advances in wireless communication and decreasing cost and size of electronic devices are promoting the appearance of large inexpensive interconnected systems, each with computational, sensing and mobile ca- bilities. This is fostering the development of many engineering applications, which exploit the availability of these systems of systems to monitor and control very large-scale phemena with ?ne resolution.
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
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Understanding Complex Systems
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Springer-Verlag Berlin and Heidelberg GmbH & Co. K