Christian L. Vielhaus

Apr 29, 2024 | fis.tu-dresden.de | Peter Sossalla |Johannes Hofer |Justus Rischke |Christian L. Vielhaus

Existing Visual Simultaneous Localization And Mapping (vSLAM) approaches that offload the complex self-localization computations from mobile robots over a wireless network to edge computing are limited to static offloading, i.e., the offloaded computation tasks are offloaded permanently.

Jul 7, 2023 | fis.tu-dresden.de | Deutsche Telekom Chair |Osel Lhamo |Johannes Busch |Christian L. Vielhaus

Machine learning (ML) equips next-generation networks with anticipatory capabilities. End-to-end predictive Quality of Service (pQoS) leverages ML models to estimate QoS indicators. In this paper, we present several ML models that can estimate the maximum achievable instantaneous throughput (link capacity) of cellular networks. The models do not only estimate the most likely value, but also quantify the uncertainty of their own estimate by providing estimated quantile values as uncertainty bounds.