Self-Assembly and Self-Organization in Complex Distributed Systems

Summary

The aim of this project is use a range of algorithmic techniques (graph theoretic, game theoretic, information theoretic) to study and gain insight into the processes of self-assembly and self-organization for a wide range of systems.

Supervisor(s)

Professor Albert Y. Zomaya, Professor Liaquat Hossain, Professor Mathew Vadas

Research Location

Charles Perkins Centre – the Judith and David Coffey Life Lab

Program Type

Masters/PHD

Synopsis

Self-assembly is the fundamental process that creates the specific conditions under which proteins, ecosystems, and societies spontaneously arrange themselves into a final entity (immune system, soil, consumers, etc). On the other hand, self-organization is a process in which the components (or state) of a system increase in complexity without external intervention. In some cases, self-organizing systems could exhibit emergent behaviour. The aim of this project is use a range of algorithmic techniques (graph theoretic, game theoretic, information theoretic) to study and gain insight into the processes of self-assembly and self-organization for a wide range of systems. Moreover, the project will attempt to explore the complex nature of computation in systems that consist of hundreds or thousands of components (e.g. networks in biology, medicine, ecosystems, trade networks, etc).

Additional Information

The Life Lab creates a new kind of graduate and postgraduate training environment at the interface between life, social, economic and physical sciences. Its focus is to address the significant challenges we face from an unsustainable food system that degrades the environmental services it depends on, and creates significant societal health problems. A better understanding of the complexity of the environment-food-health nexus is critical. It is fundamental to building a sustainable society, and one that is more robust to future uncertainties. Our unique approach will be a world-first in shifting research on these growing challenges from treating symptoms to prevention.Life Lab will challenge existing paradigms and university models to create a research training environment in which traditional disciplinary boundaries do not apply. Our ambitious vision is to create an ‘innovation hub' where researchers from disciplines spanning physical, life and social and economic sciences will interface with business, government and agency leaders. It will develop integrated approaches to the challenges that threaten societal wellbeing, and train the next generation of experts with the skills required to find solutions.

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Keywords

social networks, self-organisation, modeling, networks, health, ecosystems, economics, trade

Opportunity ID

The opportunity ID for this research opportunity is: 1683

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