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Discovering good links between objects in the internet of things

  • Francesco Buccafurri
  • , Gianluca Lax
  • , Serena Nicolazzo
  • , Antonino Nocera
  • , Luca Console
  • , Assunta Matassa

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationWINSYS
EditorsPascal Lorenz, Mohammad S. Obaidat, Enrique Cabello
PublisherSciTePress
Pages102-107
Number of pages6
ISBN (Electronic)9789897582615
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event14th International Joint Conference on e-Business and Telecommunications, ICETE 2017 - Madrid, Spain
Duration: 24 Jul 201726 Jul 2017

Publication series

NameICETE 2017 - Proceedings of the 14th International Joint Conference on e-Business and Telecommunications
Volume6

Conference

Conference14th International Joint Conference on e-Business and Telecommunications, ICETE 2017
Country/TerritorySpain
CityMadrid
Period24/07/1726/07/17

Keywords

  • Assortativity
  • Internet of Things
  • Network Efficiency
  • Twitter

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