Time-Optimized Contextual Information Flow on Unmanned Vehicles

Panagidi, K., Galanis, I., Anagnostopoulos, C. and Hadjiefthymiades, S. (2018) Time-Optimized Contextual Information Flow on Unmanned Vehicles. In: IEEE 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2018), Limassol, Cyprus, 15-17 Oct 2018, pp. 185-191. ISBN 9781538668764 (doi: 10.1109/WiMOB.2018.8589172)

167354.pdf - Accepted Version



Nowadays, the domain of robotics experiences a significant growth. We focus on Unmanned Vehicles intended for the air, sea and ground (UxV). Such devices are typically equipped with numerous sensors that detect contextual parameters from the broader environment, e.g., obstacles, temperature. Sensors report their findings (telemetry) to other systems, e.g., back-end systems, that further process the captured information while the UxV receives control inputs, such as navigation commands from other systems, e.g., commanding stations. We investigate a framework that monitors network condition parameters including signal strength and prioritizes the transmission of control messages and telemetry. This framework relies on the Theory of Optimal Stopping to assess in real-time the trade-off between the delivery of the messages and the network quality statistics and optimally schedules critical information delivery to back-end systems.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Anagnostopoulos, Dr Christos
Authors: Panagidi, K., Galanis, I., Anagnostopoulos, C., and Hadjiefthymiades, S.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2018 IEEE
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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