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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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Buccafurri, F.; Lax, G.; Nicolazzo, S.; Nocera, A.; Console, L. and Matassa, A. (2017). Discovering Good Links Between Objects in the Internet of Things. In Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - WINSYS; ISBN 978-989-758-261-5; ISSN 2184-3236, SciTePress, pages 102-107. DOI: 10.5220/0006475601020107

@conference{winsys17,
author={Francesco Buccafurri. and Gianluca Lax. and Serena Nicolazzo. and Antonino Nocera. and Luca Console. and Assunta Matassa.},
title={Discovering Good Links Between Objects in the Internet of Things},
booktitle={Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - WINSYS},
year={2017},
pages={102-107},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006475601020107},
isbn={978-989-758-261-5},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - WINSYS
TI - Discovering Good Links Between Objects in the Internet of Things
SN - 978-989-758-261-5
IS - 2184-3236
AU - Buccafurri, F.
AU - Lax, G.
AU - Nicolazzo, S.
AU - Nocera, A.
AU - Console, L.
AU - Matassa, A.
PY - 2017
SP - 102
EP - 107
DO - 10.5220/0006475601020107
PB - SciTePress