Optimizing Real-Time Decision-Making in Sensor Networks
| dc.contributor.author | Yiǧitbaşi,Y. | |
| dc.contributor.author | Stroppa,F. | |
| dc.contributor.author | Badia,L. | |
| dc.contributor.other | Computer Engineering | |
| dc.contributor.other | 05. Faculty of Engineering and Natural Sciences | |
| dc.contributor.other | 01. Kadir Has University | |
| dc.date.accessioned | 2024-06-23T21:38:36Z | |
| dc.date.available | 2024-06-23T21:38:36Z | |
| dc.date.issued | 2023 | |
| dc.description | Alnoor University College; University of Anbar; University Technology of Iraq; Wasit University | en_US |
| dc.description.abstract | The rapid integration of digital technologies into physical systems has given rise to cyber-physical systems, where the interaction between the computational and physical components plays a crucial role. This study explores optimal decision-making in event detection and transmission scheduling within cyber-physical systems, emphasizing the crucial aspect of efficient decision-making. We consider the problem of monitoring and reporting about a single event taking place within a finite time window achieving a reward related to the timeliness of the status update. Thus, the objective corresponds to minimizing the age of information between the instant of the event x and the status update time t, with a further penalty for a missed event. The monitoring apparatus decides when to perform the status update without knowing the value of x, but only knowing its statistical distribution. We assume a triangular probability density function for the instant of the event taking place, with a variable average. We provide an analytical derivation of the optimal choice of the status update, highlighting interesting trends, such as the saturation in the value of t as x grows close to the limit of the observation window. This proposed problem and its analytical formalization may serve as a further foundation for the general analysis of optimal monitoring of cyber-physical systems. © 2023 IEEE. | en_US |
| dc.identifier.citationcount | 0 | |
| dc.identifier.doi | 10.1109/DeSE60595.2023.10469190 | |
| dc.identifier.isbn | 979-835038134-4 | |
| dc.identifier.issn | 2161-1343 | |
| dc.identifier.scopus | 2-s2.0-85189341041 | |
| dc.identifier.uri | https://doi.org/10.1109/DeSE60595.2023.10469190 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12469/5815 | |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | Proceedings - International Conference on Developments in eSystems Engineering, DeSE -- 16th International Conference on Developments in eSystems Engineering, DeSE 2023 -- 18 December 2023 through 20 December 2023 -- Istanbul -- 198346 | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Age of Information | en_US |
| dc.subject | Internet of Things | en_US |
| dc.subject | Optimal Transmission Scheduling | en_US |
| dc.subject | Sensor Networks | en_US |
| dc.title | Optimizing Real-Time Decision-Making in Sensor Networks | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
| gdc.author.institutional | Stroppa, Fabıo | |
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| gdc.description.department | Kadir Has University | en_US |
| gdc.description.departmenttemp | Yiǧitbaşi Y., Kadir Has University, Dept. of Computer Engineering, Istanbul, Turkey; Stroppa F., Kadir Has University, Dept. of Computer Engineering, Istanbul, Turkey; Badia L., University of Padova, Dept. of Information Engineering (DEI), Italy | en_US |
| gdc.description.endpage | 211 | en_US |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| gdc.description.startpage | 206 | en_US |
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| gdc.oaire.keywords | Age of Information; Internet of Things; Optimal Transmission Scheduling; Sensor Networks | |
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