Title
Self-Organising Semantic Resource Discovery for Pervasive Systems
Abstract
The pervasive computing vision encompasses scenarios where services are delivered to users as a result of opportunistic encounters between their personal devices and computational resources embedded in their surrounding environment. The decentralised and dynamic nature of such environments complicates service provision, providing no setting for a conventional orchestrator to manage the resource discovery process. This paper proposes a novel approach to resource discovery, employing nature-inspired patterns to manage the search for and retrieval of information across a dynamic arrangement of devices. We show how the results of fuzzy matching based on semantic resource descriptions can be incorporated at the pattern level to route only the best matched resources to a requestor, and how application context extrinsic to the matching algorithm may augment this process.
Year
DOI
Venue
2012
10.1109/SASOW.2012.39
SASO Workshops
Keywords
Field
DocType
application context extrinsic,matching algorithm,self-organising semantic resource discovery,computational resource,resource discovery process,resource discovery,conventional orchestrator,dynamic nature,fuzzy matching,pervasive systems,dynamic arrangement,semantic resource description,ubiquitous computing,pattern matching,fuzzy set theory,information retrieval,resource allocation
World Wide Web,Computer science,Human–computer interaction,Resource allocation,Orchestration,Approximate string matching,Ubiquitous computing,Business process discovery,Pattern matching,Blossom algorithm,Semantic matching,Distributed computing
Conference
ISSN
ISBN
Citations 
1949-3673
978-1-4673-5153-9
6
PageRank 
References 
Authors
0.44
11
5
Name
Order
Citations
PageRank
Graeme Stevenson125615.21
Juan Ye242429.23
Simon Dobson3112560.75
Mirko Viroli42278156.77
Sara Montagna534523.45