Authors:
Francesco Buccafurri
1
;
Gianluca Lax
1
;
Serena Nicolazzo
1
;
Antonino Nocera
1
;
Luca Console
2
and
Assunta Matassa
2
Affiliations:
1
University of Reggio Calabria, Italy
;
2
University of Torino, Italy
Keyword(s):
Internet of Things, Network Efficiency, Assortativity, Twitter.
Related
Ontology
Subjects/Areas/Topics:
Data Communication Networking
;
Enterprise Information Systems
;
Internet of Things
;
Sensor Networks
;
Software Agents and Internet Computing
;
Software and Architectures
;
Telecommunications
Abstract:
The Internet of Things is an emerging paradigm allowing the control of the physical world via the Internet
protocol and both human-to-machine and machine-to-machine communication. In this scenario, one of the
most challenging issues is how to choose links among objects in order to guarantee an effective access to
services and data. In this paper, we present a new selection criterion that improves the classical approach. To
reach this goal, we extract knowledge coming from the social network of humans, as owners of objects, and we
exploit a recently proven property called interest assortativity. The preliminary experimental results reported
in this paper give a first evidence of the effectiveness of our approach, which performs better than classical
strategies. This is achieved by choosing only not redundant links in such a way that network connectivity is
preserved and power consumption is reduced.