Self Organization in Coordination Systems using a WordNet-based Ontology

Sascia Virruso, Danilo Pianini  /  Andrea Omicini, Mirko Viroli, Sascia Virruso, Danilo Pianini, Ronaldo Menezes

In today's data-intensive world, the need for data
organization has increased dramatically. Distributed systems
are dealing with unheard amounts of data arising primarily
from the popularization of pervasive computing applications
and the so-called "data-in-the-cloud" paradigm. Naturally, agentcoordination
systems are affected by this data-increase phenomenon
as they are often used as the basis for pervasivecomputing
frameworks and cloud-computing systems. There have
been a few works on coordination system to include data selforganization
(e.g. SwarmLinda) however they generally organize
their data based on naive approaches where items are either
completely similar or dissimilar (1j0 approach for matching
of data). Although this approach is useful, in general-purpose
systems where the diversity of data items is large, data items
will rarely be considered as plainly similar, leading to a situation
where data does not self-organize well. In this paper we move
towards a general-purpose approach to organization based on
an ontology-defined concept relationship in WordNet. In our
approach, data items are seen as concepts that have relation to
other concepts: tuples are driven towards one-another at rates
that are proportional to the strength of tuple relationship. We
demonstrate that this approach leads to a good mechanism to
self-organize data in data-intensive environments.

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