DocumentCode
2992729
Title
Self Organization in Coordination Systems Using a WordNet-Based Ontology
Author
Pianini, Danilo ; Virruso, Sascia ; Menezes, Ronaldo ; Omicini, Andrea ; Viroli, Mirko
Author_Institution
Alma Mater Studiorum, Univ. di Bologna, Bologna, Italy
fYear
2010
fDate
Sept. 27 2010-Oct. 1 2010
Firstpage
114
Lastpage
123
Abstract
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, agent-coordination systems are affected by this data-increase phenomenon as they are often used as the basis for pervasive-computing frameworks and cloud-computing systems. There have been a few works on coordination system to include data self-organization (e.g. Swarm Linda) however they generally organize their data based on naive approaches where items are either completely similar or dissimilar (1|0 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.
Keywords
Internet; data handling; distributed processing; ontologies (artificial intelligence); software agents; ubiquitous computing; WordNet-based ontology; agent-coordination systems; cloud-computing systems; coordination systems; data organization; data-in-the-cloud paradigm; data-intensive environments; distributed systems; pervasive-computing frameworks; Animals; Artificial neural networks; Databases; Ontologies; Organizations; Semantics; Standards organizations; Coordination; Data-intensive environments; Self-organization; TuCSoN; WordNet; tuple spaces;
fLanguage
English
Publisher
ieee
Conference_Titel
Self-Adaptive and Self-Organizing Systems (SASO), 2010 4th IEEE International Conference on
Conference_Location
Budapest
Print_ISBN
978-1-4244-8537-6
Electronic_ISBN
978-0-7695-4232-4
Type
conf
DOI
10.1109/SASO.2010.35
Filename
5630506
Link To Document