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Digital Library

of the European Council for Modelling and Simulation

 

Title:

A DSL-based modeling approach for energy harvesting IoT/WSN

Authors:

Lelio Campanile, Mauro Iacono, Fiammetta Marulli,
Marco Gribaudo, Michele Mastrioianni

Published in:

 

 

(2022). ECMS 2022, 36th Proceedings
Edited by: Ibrahim A. Hameed, Agus Hasan, Saleh Abdel-Afou Alaliyat, European Council for Modelling and Simulation.

 

DOI: http://doi.org/10.7148/2022

ISSN: 2522-2422 (ONLINE)

ISSN: 2522-2414 (PRINT)

ISSN: 2522-2430 (CD-ROM)

 

ISBN: 978-3-937436-77-7
ISBN: 978-3-937436-76-0(CD)

 

Communications of the ECMS , Volume 36, Issue 1, June 2022,

Ålesund, Norway May 30th - June 3rd, 2022

 

Citation format:

Lelio Campanile, Mauro Iacono, Fiammetta Marulli, Marco Gribaudo, Michele Mastrioianni (2022). A DSL-based modeling approach for energy harvesting IoT/WSN, ECMS 2022 Proceedings Edited By: Ibrahim A. Hameed, Agus Hasan, Saleh Abdel-Afou Alaliyat, European Council for Modeling and Simulation.

doi:10.7148/2022-0317

DOI:

https://doi.org/10.7148/2022-0317

Abstract:

The diffusion of intelligent services and the push for the integration of computing systems and services in the environment in which they operate require a constant sensing activity and the acquisition of different information from the environment and the users. Health monitoring, domotics, Industry 4.0 and environmental challenges leverage the availability of cost-effective sensing solutions that allow both the creation of knowledge bases and the automatic process of them, be it with algorithmic approaches or artificial intelligence solutions. The foundation of these solutions is given by the Internet of Things (IoT), and the substanding Wireless Sensor Networks (WSN) technology stack. Of course, design approaches are needed that enable defining efficient and effective sensing infrastructures, including energy related aspects.

In this paper we present a Domain Specific Language for the design of energy aware WSN IoT solutions, that allows domain experts to define sensor network models that may be then analyzed by simulation-based or analytic techniques to evaluate the effect of task allocation and offloading and energy harvesting and utilization in the network. The language has been designed to leverage the SIMTHESys modeling framework and its multiformalism modeling evaluation features.

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