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Adaptive multi-hop networks for industrial applications with dynamically changing traffic
Citation Link: https://doi.org/10.15480/882.5080
Publikationstyp
Doctoral Thesis
Date Issued
2023
Sprache
English
Author(s)
Advisor
Referee
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2022-12-20
Institut
TORE-DOI
Citation
Technische Universität Hamburg (2023)
This dissertation explores techniques for adaptive multi-hop networks in the IIoT concerning time-varying, dynamically changing traffic. It demonstrates that efficient transmission of management traffic is crucial for high adaptability in IEEE 802.15.4 DSME, develops several techniques to increase adaptability and validates them through simulations, hardware experiments, and analytical models. In particular, QMA reduces collisions in management traffic by learning when it is feasible to transmit a packet. Sending multiple packets per GTS and group acknowledgments further relieve the management traffic load. Finally, dynamic CAP-reduction enables a fine-grained trade-off between management and data traffic.
Subjects
Industrial internet of things
Wireless sensor networks
IEEE 802.15.4 DSME
Industry 4.0
Machine learning
network simulation
DDC Class
620: Ingenieurwissenschaften
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Name
Florian_Meyer_Adaptive_Multi-hop_Networks_For_Industrial_Applications_With_Dynamically_Changing_Traffic.pdf
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8.16 MB
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