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January 2018

Communications of the ACM

Communications of the ACM

Researchers at the University of Liverpool have had their review article titled “Elements of the Theory of Dynamic Networks” published in the February issue of Communications of the ACM. The article is authored by members of the Department of Computer Science at the University of Liverpool, Othon Michail and Paul Spirakis. The article, that looks into various lines of research on dynamic networks including the authors’ own work on the subject, is accompanied by a video that features Othon and Paul discussing the importance of developing a theory of dynamic networks as well as the main challenges and implications.

Elements of the Theory of Dynamic Networks: The challenge of computing in a highly dynamic environment. 

A dynamic network is a network that changes with time. Nature, society, and the modern communications landscape abound with examples. Molecular interactions, chemical reactions, social relationships and interactions in human and animal populations, transportation networks, mobile wireless devices, and robot collectives form only a small subset of the systems whose dynamics can be naturally modeled and analyzed by some sort of dynamic network. Though many of these systems have always existed, it was not until recently the need for a formal treatment that would consider time as an integral part of the network has been identified. Computer science is leading this major shift, mainly driven by the advent of low-cost wireless communication devices and the development of efficient wireless communication protocols.


Key Insights:

-          We are rapidly approaching the era of dynamicity and of the highly unpredictable. A great variety of modern networked systems are highly dynamic both in space and time.

-          Theory will continue sitting at the center of progress in our science and its necessity toward our understanding of dynamic networks is already evident.

-          Many traditional approaches and measures for static networks are not adequate for dynamic networks. There is already strong evidence that there is room for the development of a rich theory.

-          Despite the considerable recent progress discussed in this article, we do not yet really know how to compute in highly dynamic environments.

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