Links zu weiteren Portalen

Seiteninterne Suche

Publications

DynDSE: Automated Multi-Objective Design Space Exploration for Context-Adaptive Wearable IoT Edge Devices

Publication Type Journal Article
Authors Giovanni Schiboni, Juan Carlos Suarez, Rui Zhang, Oliver Amft
Title DynDSE: Automated Multi-Objective Design Space Exploration for Context-Adaptive Wearable IoT Edge Devices
Abstract We describe a simulation-based Design Space Exploration procedure (DynDSE) for wearable IoT edge devices that retrieve events from streaming sensor data using context-adaptive pattern recognition algorithms. We provide a formal characterisation of the design space, given a set of system functionalities, components and their parameters. An iterative search evaluates configurations according to a set of requirements in simulations with actual sensor data. The inherent trade-offs embedded in conflicting metrics are explored to find an optimal configuration given the application-specific conditions. Our metrics include retrieval performance, execution time, energy consumption, memory demand, and communication latency. We report a case study for the design of electromyographic-monitoring eyeglasses with applications in automatic dietary monitoring. The design space included two spotting algorithms, and two sampling algorithms, intended for real-time execution on three microcontrollers. DynDSE yielded configurations that balance retrieval performance and resource consumption with an F1 score above 80% at an energy consumption that was 70% below the default, non-optimised configuration. We expect that the DynDSE approach can be applied to find suitable wearable IoT system designs in a variety of sensor-based applications.
Publication Sensors
Volume 20
Issue 21
Pages 6104
Date 2020
Language en
DOI 10.3390/s20216104
Short Title DynDSE
URL Publisher's website
Accessed 2020-10-28T11:01:51Z
Library Catalog www.mdpi.com
Rights http://creativecommons.org/licenses/by/3.0/
Full Text PDF