Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/6C42E71B-EED2-4535-AD1F-F24F8F5E0D02 | - |
| Αναγνωριστικό | https://doi.org/10.1109/JIOT.2023.3265423 | - |
| Αναγνωριστικό | https://ieeexplore.ieee.org/document/10097494 | - |
| Γλώσσα | en | - |
| Μέγεθος | 18 pages | en |
| Τίτλος | Design and implementation of ambiently powered Internet of Things-That-Think with asynchronous inference | en |
| Δημιουργός | Papageorgiou Vasileios | en |
| Δημιουργός | Παπαγεωργιου Βασιλειος | el |
| Δημιουργός | Nichoritis Athanasios | en |
| Δημιουργός | Νηχωριτης Αθανασιος | el |
| Δημιουργός | Vasilakopoulos Panagiotis | en |
| Δημιουργός | Βασιλακοπουλος Παναγιωτης | el |
| Δημιουργός | Vougioukas Georgios | en |
| Δημιουργός | Βουγιουκας Γεωργιος | el |
| Δημιουργός | Bletsas Aggelos | en |
| Δημιουργός | Μπλετσας Αγγελος | el |
| Εκδότης | Institute of Electrical and Electronics Engineers | en |
| Περιγραφή | This work was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) through the “First Call for H.F.R.I. Research Projects to support Faculty Members and Researchers and the Procurement of High-Cost Research Equipment” under Project 2846. This article was presented in part at 5th IEEE International Workshop on Wireless Communications and Networking in Extreme Environments (WCNEE), International Conference on Distributed Computing in Sensor Systems (DCOSS), Pafos, Cyprus, July 2021, pp. 458–465 [DOI: 10.1109/DCOSS52077.2021.00077]. (Vasileios Papageorgiou, Athanasios Nichoritis, and Panagiotis Vasilakopoulos contributed equally to this work.) (Corresponding author: Aggelos Bletsas.) | en |
| Περίληψη | This work offers design and implementation of in-network inference, using message passing among ambiently powered wireless sensor network (WSN) terminals. The stochastic nature of ambient energy harvesting dictates intermittent operation of each WSN terminal and as such, the message passing inference algorithms should be robust to asynchronous operation. 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, in-network message passing problem, often at the expense of increased total delay. Examples from Gaussian belief propagation and average consensus (AC) are provided, along with the derivation of a statistical convergence metric for the latter case. A k-means method is offered that maps the elements of the calculated vector to the different WSN terminals and overall execution delay (in number of iterations) is quantified. Interestingly, it is shown that there are divergent instances of the in-network message passing algorithms that become convergent, under asynchronous operation. Ambient solar energy harvesting availability is also studied, controlling the probability of successful (or not) message passing. Hopefully, this work will spark further interest for asynchronous message passing algorithms and technologies that enable in-network inference, toward ambiently powered, batteryless Internet of Things-That-Think. | en |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2025-04-25 | - |
| Ημερομηνία Δημοσίευσης | 2023 | - |
| Θεματική Κατηγορία | Distributed signal processing | en |
| Θεματική Κατηγορία | Energy harvesting | en |
| Θεματική Κατηγορία | In situ processing | en |
| Θεματική Κατηγορία | Low-cost sensors and device | en |
| Θεματική Κατηγορία | Resourceconstrained networks | en |
| Βιβλιογραφική Αναφορά | V. Papageorgiou, A. Nichoritis, P. Vasilakopoulos, G. Vougioukas and A. Bletsas, "Design and implementation of ambiently powered Internet of Things-That-Think with asynchronous inference," IEEE Internet Things J., vol. 10, no. 17, pp. 15283-15300, Sep. 2023, doi: 10.1109/JIOT.2023.3265423. | en |
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