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Content archived on 2024-05-27

Biology-Inspired techniques for Self-Organization in dynamic Networks


BISON will explore the use of ideas derived from complex adaptive systems (CAS) to enable the construction of robust and self-organizing information systems for deployment in highly dynamic network environments. BISON will cast solutions to important problems arising in Ad-Hoc and Virtual networks, P2P and Grid computing systems as desirable global properties that systems should exhibit. We will then search for CAS, which can bring about these global properties. Yet BISON will seek to go even further by working to systematize this process to develop a coherent set of heuristics that can guide the search for CAS giving a desired global behaviour. Progress in this direction will give us a systematic framework for constructing solutions to the original problem that inherit the attributes of CAS, including self-repair and self-organization. We expect to achieve this goal by restricting the class of problems and by drawing inspiration from natural systems like insect colonies and immune networks.

The complexity of modern Network Information Systems (NIS) has reached a level that puts them beyond our ability to deploy, manage and keep functioning correctly through traditional techniques. Part of the problem is due to the sheer size that these systems may reach with millions of users and millions of interconnected devices. The other aspect of the problem is due to the extremely complex interactions that may result among components even when their numbers are modest. Our current understanding of these systems is such that minor perturbations in some remote corner of the system will often have unforeseen, and at times catastrophic, global repercussions. In addition to being fragile, many situations arising from the highly dynamic environment in which they are deployed require manual intervention to keep NIS functioning. What is required is a paradigm shift in confronting the complexity explosion problem to enable building robust NIS that are self-organizing and self-repairing. BISON proposes to draw inspiration from biological processes and develop techniques and tools for building robust, self-organizing and self-repairing NIS as ensembles of autonomous agents that mimic the behaviour of social insects and immune networks. What renders this approach particularly attractive from a dynamic network perspective is that global properties like adaptation, self-organization and robustness are achieved without explicitly programming them into the individual artificial agents. Yet, given large enough colonies of agents, the global behaviour is surprisingly adaptive and can cope with arbitrary initial conditions, unforeseen scenarios, and variations in the environment or presence of deviant agents. This represents a radical shift from traditional algorithmic techniques to that of obtaining the desired system properties as a result of emergent behaviour that often involves evolution, adaptation, or learning.

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