BETaaS: A Platform for Development and Execution of Machine-to-Machine Applications in the Internet of Things

Carlo Vallati, Enzo Mingozzi, Giacomo Tanganelli, Novella Buonaccorsi, Nicola Valdambrini, Nikolaos Zonidis, Belén Martínez, Alessandro Mamelli, Davide Sommacampagna, Bayu Anggorojati, Sofoklis Kyriazakos, Neeli Prasad, Francisco Javier Nieto, Oliver Barreto Rodriguez

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

The integration of everyday objects into the Internet represents the foundation of the forthcoming Internet of Things (IoT). Smart objects will be the building blocks of the next generation of applications that will exploit interaction between machines to implement enhanced services with minimum or no human intervention in the loop. A crucial factor to enable Machine-to-Machine (M2M) applications is a horizontal service infrastructure that seamlessly integrates existing IoT heterogeneous systems. The authors present BETaaS, a framework that enables horizontal M2M deployments. BETaaS is based on a distributed service infrastructure built on top of an overlay network of gateways that allows seamless integration of existing IoT systems. The platform enables easy deployment of applications by exposing to developers a service oriented interface to access things (according to a Things-as-a-Service model) regardless of the technology and the physical infrastructure they belong to.

Original languageEnglish
Pages (from-to)1071-1091
Number of pages21
JournalWireless Personal Communications
Volume87
Issue number3
DOIs
Publication statusPublished - 1 Apr 2016

Keywords

  • Context awareness
  • Fog computing
  • IoT platforms
  • Local cloud
  • M2M

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    Vallati, C., Mingozzi, E., Tanganelli, G., Buonaccorsi, N., Valdambrini, N., Zonidis, N., Martínez, B., Mamelli, A., Sommacampagna, D., Anggorojati, B., Kyriazakos, S., Prasad, N., Nieto, F. J., & Rodriguez, O. B. (2016). BETaaS: A Platform for Development and Execution of Machine-to-Machine Applications in the Internet of Things. Wireless Personal Communications, 87(3), 1071-1091. https://doi.org/10.1007/s11277-015-2639-0