Internet of Things (IoT) applications operate in several domains while requiring seamless integration among heterogeneous objects. Regardless of the specific platform and context, IoT applications demand high energy efficiency. Adopting resource-constrained embedded devices for IoT applications means ensuring low power consumption, low maintenance costs and possibly longer battery life. Meeting these requirements is particularly arduous as programmers are not able to monitor the energy consumption of their own software during development or when applications are finally deployed. In this paper, we discuss on-board real-time energy evaluation of both hardware and software during the development phases and prospect the inclusion of energy-aware capabilities into symbolic execution models for resource-constrained devices, which have not been widely explored before. To provide baseline estimations, tests were carried out on different hardware and software configurations.

Bordonaro A., Gaglio S., Lo Re G., Martorella G., & Peri D. (2020). On-board Energy Consumption Assessment for Symbolic Execution Models on Embedded Devices. In IEEE International Conference on Emerging Technologies and Factory Automation, ETFA (pp. 1359-1362). Institute of Electrical and Electronics Engineers Inc. [10.1109/ETFA46521.2020.9211981].

On-board Energy Consumption Assessment for Symbolic Execution Models on Embedded Devices

Bordonaro A.;Gaglio S.;Lo Re G.;Martorella G.;Peri D.
2020

Abstract

Internet of Things (IoT) applications operate in several domains while requiring seamless integration among heterogeneous objects. Regardless of the specific platform and context, IoT applications demand high energy efficiency. Adopting resource-constrained embedded devices for IoT applications means ensuring low power consumption, low maintenance costs and possibly longer battery life. Meeting these requirements is particularly arduous as programmers are not able to monitor the energy consumption of their own software during development or when applications are finally deployed. In this paper, we discuss on-board real-time energy evaluation of both hardware and software during the development phases and prospect the inclusion of energy-aware capabilities into symbolic execution models for resource-constrained devices, which have not been widely explored before. To provide baseline estimations, tests were carried out on different hardware and software configurations.
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Bordonaro A., Gaglio S., Lo Re G., Martorella G., & Peri D. (2020). On-board Energy Consumption Assessment for Symbolic Execution Models on Embedded Devices. In IEEE International Conference on Emerging Technologies and Factory Automation, ETFA (pp. 1359-1362). Institute of Electrical and Electronics Engineers Inc. [10.1109/ETFA46521.2020.9211981].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/437996
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