loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

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

ISBN: 978-989-758-261-5

ISSN: 2184-2825

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.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.239.45.252

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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 - Volume 5: WINSYS, (ICETE 2017) ISBN 978-989-758-261-5, ISSN 2184-2825, 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 - Volume 5: WINSYS, (ICETE 2017)},
year={2017},
pages={102-107},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006475601020107},
isbn={978-989-758-261-5},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on e-Business and Telecommunications - Volume 5: WINSYS, (ICETE 2017)
TI - Discovering Good Links Between Objects in the Internet of Things
SN - 978-989-758-261-5
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

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.