Meyer, FlorianFlorianMeyerTurau, VolkerVolkerTurau2020-12-102020-12-102020-02GI/ITG KuVS Fachgespräche Machine Learning and Networking (2020)http://hdl.handle.net/11420/8185The rise of wireless sensor networks (WSNs) inindustrial applications imposes novel demands on existing wire-less protocols. Thedeterministic and synchronous multi-channelextension(DSME) is a recent amendment to the IEEE 802.15.4standard, which aims for highly reliable, deterministic trafficin these industrial environments. It offers TDMA-based channelaccess, where slots are allocated in a distributed manner. In thiswork, we propose a novel scheduling algorithm for DSME whichminimizes the delay in time-critical applications by employingreinforcement learning (RL) on deep neural networks (DNN).enMLE@TUHHConference Paperhttps://www.ti5.tuhh.de/publications/2020/meyer_kuvs_mlvs.pdfConference Paper