cogcom 15(2): e6

Research Article

High-level Programming and Symbolic Reasoning on IoT Resource Constrained Devices

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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
Sal vatore Gaglio1,2, Giuseppe Lo Re2, Gloria Martorella2, Daniele Peri2,*
  • 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.