In 1952 A. Turin published a paper ‘The Chemical Basis of Morphogenesis’ which was a milestone for the development of mathematical biology and for many other disciplines. He proposed an original solution to the problem of morphogenesis, by adapting a system of coupled differential equations to describe both chemical reaction and diffusion of morphogenetic substances in an initially homogeneous configuration. He was clearly determined to provide an argument for the generation of ‘order-from-disorder’: explaining how a chemical soup of molecules could possibly give rise to a biological pattern, given the transcription of genes into diffusible molecules. One of the examples he suggested was the formation of the radiolarian skeleton.

Radiolarian skeleton: the preferred case study of A.Turing

Imagine future networks as “soups” of (communication and processing) resources. Actually already today we are living in an increasingly interconnected world and it is reasonable to imaging tomorrow networks characterized by such abundance of pervasively distributed resources around us. Understanding and simplifying the complexity of these “soups of resources” are crucial issues for managing socio-technical systems and the dynamical processes running on top of them.

Interestingly, this paper elaborates about that. It is shown how emergence of collective behavior in complex systems and networks is allowing us to adopt a route analysis which essentially similar to the statistical physics. Example are the reaction-diffusion processes, the same studied by A. Turing. Very similar spreading models can adopted for the description of the diffusion of both real pathogens and pieces of information in complex networks. The analysis of the adaptive behavior of the individuals to these dynamical processes is still an open challenge: for instance, little work has been done to coupled reaction diffusion processes with (autonomic) behavioral adaptation of individuals, and the related emergent properties, as triggered by the perception of pathogens’ (e.g. pieces of information, knowledge) spreading.

These researches are moving towards understanding how the emergent properties in complex networks impact their controllability and vice versa how we can direct emergence: I see them as hot topics for managing future socio-technical systems and applications.