High-level Programming and Symbolic Reasoning on IoT Resource Constrained Devices (original) (raw)

cogcom 15(2): e6

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• @ARTICLE{10.4108/cogcom.1.2.e6,
  author={Sal vatore Gaglio and Giuseppe Lo Re and Gloria Martorella and Daniele Peri},
  title={High-level Programming and Symbolic Reasoning on IoT Resource Constrained Devices},
  journal={EAI Endorsed Transactions on Cognitive Communications},
  volume={1},
  number={2},
  publisher={ICST},
  journal_a={COGCOM},
  year={2015},
  month={5},
  keywords={High-level programming, Resource constrained devices, Knowledge Representation, Fuzzy Logic.},
  doi={10.4108/cogcom.1.2.e6}
  }

• Sal vatore Gaglio
  Giuseppe Lo Re
  Gloria Martorella
  Daniele Peri
  Year: 2015
  High-level Programming and Symbolic Reasoning on IoT Resource Constrained Devices
  COGCOM
  ICST
  DOI: 10.4108/cogcom.1.2.e6

• 1: ICAR CNR, Viale delle Scienze, Ed. 11, 90128 Palermo, Italy

• 2: DICGIM University of Palermo,Viale delle Scienze, Ed. 6, 90128 Palermo, Italy

*Contact email: daniele.peri@unipa.it

Abstract

While the vision of Internet of Things (IoT) is rather inspiring, its practical implementation remains challenging. Conventional programming approaches prove unsuitable to provide IoT resource constrained devices with the distributed processing capabilities required to implement intelligent, autonomic, and self-organizing behaviors. In our previous work, we had already proposed an alternative programming methodology for such systems that is characterized by high-level programming and symbolic expressions evaluation, and developed a lightweight middleware to support it. Our approach allows for interactive programming of deployed nodes, and it is based on the simple but e ective paradigm of executable code exchange among nodes. In this paper, we show how our methodology can be used to provide IoT resource constrained devices with reasoning abilities by implementing a Fuzzy Logic symbolic extension on deployed nodes at runtime.

Keywords

High-level programming, Resource constrained devices, Knowledge Representation, Fuzzy Logic.

Received

2014-12-22

Accepted

2015-03-10

Published

2015-05-28

Publisher

ICST

http://dx.doi.org/10.4108/cogcom.1.2.e6

Copyright © 2015 D. Peri et al., licensed to ICST. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.