Optimizing Real-Time Decision-Making in Sensor Networks

dc.authorscopusid58967436200
dc.authorscopusid54891556200
dc.authorscopusid7004191275
dc.contributor.authorStroppa, Fabıo
dc.contributor.authorStroppa,F.
dc.contributor.authorBadia,L.
dc.date.accessioned2024-06-23T21:38:36Z
dc.date.available2024-06-23T21:38:36Z
dc.date.issued2023
dc.departmentKadir Has Universityen_US
dc.department-tempYiǧitbaşi 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), Italyen_US
dc.descriptionAlnoor University College; University of Anbar; University Technology of Iraq; Wasit Universityen_US
dc.description.abstractThe 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.citation0
dc.identifier.doi10.1109/DeSE60595.2023.10469190
dc.identifier.endpage211en_US
dc.identifier.isbn979-835038134-4
dc.identifier.issn2161-1343
dc.identifier.scopus2-s2.0-85189341041
dc.identifier.scopusqualityN/A
dc.identifier.startpage206en_US
dc.identifier.urihttps://doi.org/10.1109/DeSE60595.2023.10469190
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5815
dc.identifier.wosqualityN/A
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 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 -- 198346en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAge of Informationen_US
dc.subjectInternet of Thingsen_US
dc.subjectOptimal Transmission Schedulingen_US
dc.subjectSensor Networksen_US
dc.titleOptimizing Real-Time Decision-Making in Sensor Networksen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
relation.isAuthorOfPublicationf8babe23-f015-4905-a50a-4e9567f9ee8d
relation.isAuthorOfPublication.latestForDiscoveryf8babe23-f015-4905-a50a-4e9567f9ee8d

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