Ευστάθιος Χατζηευθυμιάδης, Αναπληρωτής Καθηγητής, Τμήμα Πληροφορικής και Τηλεπικοινωνιών, Εθνικό και Καποδιστριακό Πανεπιστήμιο Αθηνών
Nowadays, the domain of robotics experiences a significant growth. Until now, most robots were found in the form of industrial machines. In recent years, smaller scale robotic systems have appeared, like driverless cars, drones etc. In this thesis we focus our attention 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, etc. UxV reports its sensors findings (telemetry) to other systems, e.g., back-end systems, that further process the captured information. At the same time 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 such as signal strength and prioritizes the transmission of control messages and telemetry. This framework relies on the theory of optimal stopping, which is concerned with the problem of choosing a time to take a particular acction in order to maximize an expexted reward or minimize an expected cost. We apply the optimal stopping theory to online assess the trade-off between the delivery of the messages and the network quality statistics and optimally schedule critical information delivery to back-end systems.
Ad-hoc, sensor, mesh and vehicular wireless networks; Context-awareness in wireless, mobile and multimedia networks; Device-to-device Communications