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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/54FB21E3-0EFE-4364-AB50-474C8BF371AF | - |
| Identifier | https://doi.org/10.1109/DCOSS52077.2021.00077 | - |
| Identifier | https://ieeexplore.ieee.org/document/9600006 | - |
| Language | en | - |
| Extent | 8 pages | en |
| Title | Towards ambiently powered inference on wireless sensor networks: asynchrony is the key! | en |
| Creator | Papageorgiou Vasileios | en |
| Creator | Παπαγεωργιου Βασιλειος | el |
| Creator | Nichoritis Athanasios | en |
| Creator | Νηχωριτης Αθανασιος | el |
| Creator | Vasilakopoulos Panagiotis | en |
| Creator | Βασιλακοπουλος Παναγιωτης | el |
| Creator | Vougioukas Georgios | en |
| Creator | Βουγιουκας Γεωργιος | el |
| Creator | Bletsas Aggelos | en |
| Creator | Μπλετσας Αγγελος | el |
| Publisher | Institute of Electrical and Electronics Engineers | en |
| Content Summary | Is it possible to build ultra-low power wireless sensor networks (WSN) that exploit the inherent parallel and distributed nature of powerful message passing/inference algorithms, embrace ultra-low power communication principles and make autonomous, in-network decisions, solely powered by the environment? While edge and cloud computing emerge, this work points towards the opposite direction, inspired by the fact that ambient energy, either from radio frequency (RF), sun, motion, temperature or even living organisms, has fixed (on average) density per surface (or volume). It is shown, perhaps for the first time in the literature (to the best of our knowledge), a proof of concept, where a WSN harvests energy from the environment and processes itself the collected information in a distributed manner, by converting the (network) inference task to a probabilistic, message passing problem. Examples from Gaussian Belief Propagation and Average Consensus are offered; ambient energy harvesting and availability are quantified, controling the probability of successful (or not) message passing. Such interrupted communication requires distributed algorithms robust to asynchrony, at the expense of increased overall delay. Simulation and experimental validation are offered in a WSN testbed with solar energy harvesting. Future work will focus on overall delay minimization. | en |
| Type of Item | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Type of Item | Conference Full Paper | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2023-05-26 | - |
| Date of Publication | 2021 | - |
| Subject | Wireless communication | en |
| Subject | Wireless sensor networks | en |
| Subject | Message passing | en |
| Subject | Solar energy | en |
| Subject | Sensor systems | en |
| Subject | Delays | en |
| Subject | Low-power electronics | en |
| Bibliographic Citation | V. Papageorgiou, A. Nichoritis, P. Vasilakopoulos, G. Vougioukas and A. Bletsas, "Towards ambiently powered inference on wireless sensor networks: asynchrony is the key!," in 2021 17th International Conference on Distributed Computing in Sensor Systems (DCOSS), Pafos, Cyprus, 2021, pp. 458-465, doi: 10.1109/DCOSS52077.2021.00077. | en |
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