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On Maximizing the Probability of Achieving Deadlines in Communication Networks

Becker, Benjamin ; Oberli, Christian ; Meuser, Tobias ; Steinmetz, Ralf (2024)
On Maximizing the Probability of Achieving Deadlines in Communication Networks.
In: Journal of Sensor and Actuator Networks, 13 (1)
doi: 10.3390/jsan13010009
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

We consider the problem of meeting deadline constraints in wireless communication networks. Fulfilling deadlines depends heavily on the routing algorithm used. We study this dependence generically for a broad class of routing algorithms. For analyzing the impact of routing decisions on deadline fulfillment, we adopt a stochastic model from operations research to capture the source-to-destination delay distribution and the corresponding probability of successfully delivering data before a given deadline. Based on this model, we propose a decentralized algorithm that operates locally at each node and exchanges information solely with direct neighbors in order to determine the probabilities of achieving deadlines. A modified version of the algorithm also improves routing tables iteratively to progressively increase the deadline achievement probabilities. This modified algorithm is shown to deliver routing tables that maximize the deadline achievement probabilities for all nodes in a given network. We tested the approach by simulation and compared it with routing strategies based on established metrics, specifically the average delay, minimum hop count, and expected transmission count. Our evaluations encompass different channel quality and small-scale fading conditions, as well as various traffic load scenarios. Notably, our solution consistently outperforms the other approaches in all tested scenarios.

Typ des Eintrags: Artikel
Erschienen: 2024
Autor(en): Becker, Benjamin ; Oberli, Christian ; Meuser, Tobias ; Steinmetz, Ralf
Art des Eintrags: Bibliographie
Titel: On Maximizing the Probability of Achieving Deadlines in Communication Networks
Sprache: Englisch
Publikationsjahr: 18 Januar 2024
Verlag: MDPI
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Journal of Sensor and Actuator Networks
Jahrgang/Volume einer Zeitschrift: 13
(Heft-)Nummer: 1
DOI: 10.3390/jsan13010009
Kurzbeschreibung (Abstract):

We consider the problem of meeting deadline constraints in wireless communication networks. Fulfilling deadlines depends heavily on the routing algorithm used. We study this dependence generically for a broad class of routing algorithms. For analyzing the impact of routing decisions on deadline fulfillment, we adopt a stochastic model from operations research to capture the source-to-destination delay distribution and the corresponding probability of successfully delivering data before a given deadline. Based on this model, we propose a decentralized algorithm that operates locally at each node and exchanges information solely with direct neighbors in order to determine the probabilities of achieving deadlines. A modified version of the algorithm also improves routing tables iteratively to progressively increase the deadline achievement probabilities. This modified algorithm is shown to deliver routing tables that maximize the deadline achievement probabilities for all nodes in a given network. We tested the approach by simulation and compared it with routing strategies based on established metrics, specifically the average delay, minimum hop count, and expected transmission count. Our evaluations encompass different channel quality and small-scale fading conditions, as well as various traffic load scenarios. Notably, our solution consistently outperforms the other approaches in all tested scenarios.

Zusätzliche Informationen:

Art.No.: 9

Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik > Multimedia Kommunikation
Hinterlegungsdatum: 23 Apr 2024 10:12
Letzte Änderung: 23 Apr 2024 10:12
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