Semantic-Functional Communications in Cyber-Physical Systems
Silva, Pedro E. Gória; Nardelli, Pedro H. J.; De Sena, Arthur S.; Siljak, Harun; Nevaranta, Niko; Marchetti, Nicola; De Souza, Rausley A. A. (2023-11-01)
Silva, Pedro E. Gória
Nardelli, Pedro H. J.
De Sena, Arthur S.
Siljak, Harun
Nevaranta, Niko
Marchetti, Nicola
De Souza, Rausley A. A.
IEEE
01.11.2023
P. E. Gória Silva et al., "Semantic-Functional Communications in Cyber-Physical Systems," in IEEE Network, vol. 38, no. 4, pp. 241-249, July 2024, doi: 10.1109/MNET.2023.3329192.
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© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists,or reuse of any copyrighted component of this work in other works.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202403212374
https://urn.fi/URN:NBN:fi:oulu-202403212374
Tiivistelmä
Abstract
This paper explores the use of semantic knowledge inherent in the cyber-physical system (CPS) being studied in order to minimize the use of explicit communication, which refers to the use of physical radio resources to transmit potentially informative data. It is assumed that the acquired data have a function in the system, usually related to its state estimation, which may trigger control actions. We propose a semantic-functional approach that can leverage semantic-enabled implicit communication while ensuring the system maintains its required functionality and performance. We illustrate the potential of this proposal through simulations of a swarm of drones jointly performing remote sensing in a given area. Our numerical results demonstrate that the proposed method offers the best design option regarding the ability to accomplish a previously established task—remote sensing in the addressed case—while minimizing the use of explicit communication by controlling the trade-offs that jointly determine the performance and effectiveness of the CPS in terms of resource utilization. In this sense, we establish a fundamental relationship among energy, communication, and functionality, considering a specific end application.
This paper explores the use of semantic knowledge inherent in the cyber-physical system (CPS) being studied in order to minimize the use of explicit communication, which refers to the use of physical radio resources to transmit potentially informative data. It is assumed that the acquired data have a function in the system, usually related to its state estimation, which may trigger control actions. We propose a semantic-functional approach that can leverage semantic-enabled implicit communication while ensuring the system maintains its required functionality and performance. We illustrate the potential of this proposal through simulations of a swarm of drones jointly performing remote sensing in a given area. Our numerical results demonstrate that the proposed method offers the best design option regarding the ability to accomplish a previously established task—remote sensing in the addressed case—while minimizing the use of explicit communication by controlling the trade-offs that jointly determine the performance and effectiveness of the CPS in terms of resource utilization. In this sense, we establish a fundamental relationship among energy, communication, and functionality, considering a specific end application.
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