Project description DEENESFRITPL For perfect computation in distributed systems Computer science and biology are increasingly convergent. In this context, distributed computing (DC) appears to provide the best approach to modelling natural processes, a method inspired by the high-level design principles of biological systems. However, a new framework is urgently needed to study complex self-organising processes in nature, as presently, DC models that consider all aspects simultaneously are lacking. The EU-funded CoCoNat project will bridge the gap through the theory of distributed synchronisation and coordination tasks in restricted models of DC using the distributed computing lens to model natural phenomena. It will also benefit several areas of engineering and computing through solving various synchronisation and coordination tasks like in cases of firefly populations or embryonic development. Show the project objective Hide the project objective Objective In recent years, an algorithmic theory of natural and biological systems has been increasingly advocated as providing a much needed framework for investigating complex self-organising processes in nature. This project contributes to this research program by employing the distributed computing lens to model natural phenomena. Biological systems exhibit many properties also studied in distributed computing: they comprise several independently acting entities, tend to operate in noisy and dynamic environments, thus requiring them to be highly-resilient and adaptive, solve intricate coordination tasks, and display sophisticated communication techniques.This project aims to develop the theory of distributed synchronisation and coordination tasks in restricted models of distributed computing. These tasks are some of the most fundamental problems in distributed computing, as they are essential in computer networks as well as numerous other areas of engineering and computing. In addition, they are ubiquitous in natural and biological systems, ranging from molecular to population-level systems, which are known to solve various synchronisation and coordination tasks: examples include symmetry-breaking during the development of the nervous system, consensus decision making in species communities, and synchronisation in firefly populations and embryonic development.Unlike computer networks, biological distributed systems have unique features: (1) the agents typically have limited computational abilities, (2) communication is unreliable and restricted, (3) the system has a dynamic spatial structure, and (4) the environment may be noisy. Currently, distributed computing models that consider all aspects simultaneously are lacking. The proposed research approaches this goal from multiple angles by developing new models and analysis methods for determining the limitations of synchronisation and related tasks in both strong and weak models of computing. Fields of science natural sciencesbiological sciencesneurobiologynatural sciencesbiological sciencesdevelopmental biologyengineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networks Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2018 - Individual Fellowships Call for proposal H2020-MSCA-IF-2018 See other projects for this call Funding Scheme MSCA-IF-EF-ST - Standard EF Coordinator INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA Net EU contribution € 174 167,04 Address Am Campus 1 3400 Klosterneuburg Austria See on map Region Ostösterreich Niederösterreich Wiener Umland/Nordteil Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 174 167,04
