TY - GEN A1 - Rotta, Randolf A1 - Schulz, Julius A1 - Naumann, Billy A1 - Chatharajupalli, Navya Sneha A1 - Nolte, Jörg A1 - Werner, Matthias T1 - B.A.T.M.A.N. Mesh Networking on ESP32’s 802.11 T2 - 2024 IEEE 49th Conference on Local Computer Networks (LCN) N2 - Mesh routing protocols are widely used in IoT and sensor networks. In recent years, the ESP32 Wi-Fi/BLE SoC became popular for prototyping IoT applications. However, the existing mesh networks for this platform lack efficient node to node communication, fast route discovery and repair, and energy efficiency. This paper addresses the formation of IEEE 802.11 based ad-hoc mesh networks without the delays inflicted by the Station to Access Point association protocol. We implemented the B.A.T.M.A.N. protocol on top of the ESP32 Wi-Fi MAC interface and integrated it into the LwIP network stack. The performance evaluation with respect to UDP/IP and TCP/IP end-to-end throughput shows the general usefulness but also identifies bottlenecks caused by limitations of the existing MAC interface. Overall, this opens an interesting opportunity for research on mesh protocols by providing a simpler platform than full featured Wi-Fi routers; and for wireless IoT applications by providing higher throughput than subGHz and BLE technologies. KW - wireless communication KW - mesh networks KW - wireless sensor networks KW - routing protocols Y1 - 2024 SN - 979-8-3503-8800-8 U6 - https://doi.org/10.1109/LCN60385.2024.10639698 SN - 2832-1421 SN - 2831-7742 SP - 1 EP - 7 PB - IEEE ER - TY - GEN A1 - Shahin, Keyvan A1 - Rotta, Randolf A1 - Archila, Oscar A1 - Mykytyn, Pavlo A1 - Nattke, Matthias A1 - Reichenbach, Marc A1 - Nolte, Jörg A1 - Natarov, Roman T1 - A Modular Communication Architecture for Adaptive UAV Swarms T2 - 2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS) N2 - Small Unmanned Aerial Vehicles (UAVs) have vast application potential from industrial logistics and disaster monitoring to smart farming, for example, to create maps with Normalized Difference Vegetation Index (NDVI) cameras and AI-based image classification or the precision spot application of fertilizers. Operating multiple UAVs in parallel, including those with different specializations, enables efficient coverage of large areas. While existing research focused mainly on predefined flight formations for swarms or autonomous missions for single UAVs, the focus of this work is on multiple UAVs with individually adaptable missions. We derive communication system requirements from swarm coordination algorithms and present a respective design. The resulting modular architecture enables future research on autonomous adaptive UAV swarms and their use as flying sensor platforms. Y1 - 2023 SN - 979-8-3503-4647-3 SN - 979-8-3503-4648-0 U6 - https://doi.org/10.1109/COINS57856.2023.10189245 PB - IEEE CY - Berlin ER - TY - GEN A1 - Chatharajupalli, Navya Sneha A1 - Rotta, Randolf A1 - Karnapke, Reinhardt A1 - Nolte, Jörg T1 - Probing considered harmful : leveraging RSSI for link quality prediction T2 - Proceedings of the IEEE 50th Conference on Local Computer Networks : LCN 2025 : October 14-16, 2025, Sydney, Australia N2 - Wireless mesh protocols that use a routing metric based on throughput or airtime require predictions about future throughput for all mesh neighbors. Typically, the Wi-Fi rate controller provides this information, and state-of-the-art rate control algorithms estimate it based on statistics from past unicast transmissions. This introduces an adverse cross-layer dependency because meaningful statistics are only available for the links that were used by the routing layer. Existing implementations either ignore this, or use other routing metrics, such as distance, or generate artificial periodic probe traffic to all neighbors. Unfortunately, probing reacts slowly to changing conditions, increases the medium contention, and can lead to overly optimistic predictions. To overcome this, we introduce an RSSI-based link quality prediction for the routing layer. Benchmarks in a B.A.T.M.A.N. version V mesh show a decrease of round-trip time by three orders of magnitude and an increase of the end-to-end packet delivery ratio. TCP connections became possible over long routes that were previously unusable. Although highly imprecise, the easy to acquire RSSI provided sufficiently good predictions for our mesh network. KW - Wireless Mesh Network KW - Multi-hop routing KW - Neural Networks KW - Machine Learning KW - Link quality predictors Y1 - 2025 SN - 979-8-3315-3704-3 U6 - https://doi.org/10.1109/LCN65610.2025.11146347 SN - 2831-7742 SP - 1 EP - 9 PB - IEEE CY - New York, NY ER - TY - GEN A1 - Chatharajupalli, Navya Sneha A1 - Rotta, Randolf A1 - Karnapke, Reinhardt A1 - Nolte, Jörg T1 - Animal health monitoring and tracking through solar-powered mesh network T2 - 22. GI/ITG KuVS Fachgespräch Sensornetze : 11. und 12. September 2025, Clausthal-Zellerfeld N2 - Various health and movement sensors, especially bolus sensors inside a cow’s stomach, are crucial for timely medical interventions. Commonly, wall-powered gateways are used to retrieve sensor updates and forward them quickly to an analysis service. In large outdoor farmlands, however, localisation of individual cows becomes important while the long-term operation of wall-powered gateways is costly. Previous solutions that use a LoRaWAN gateway with bigger antennas are still limited to 500m and provide only poor localization information. Existing solutions based on a mesh network of repeaters provide good localization but still depend on external wall power. Solar-powered mesh nodes would simplify the long-term operation. In order to achieve this, a significant improvement of the energy efficiency of the mesh nodes is necessary. This paper explores protocol design choices for the energy-efficient communication between mesh nodes and the bolus sensors. By introducing synchronised sleep and communication intervals, the size of the solar panels and energy storage can be reduced. KW - Wireless Networks KW - Solar-harvesting KW - Localisation Y1 - 2025 UR - https://dokumente.ub.tu-clausthal.de/receive/clausthal_mods_00002954 U6 - https://doi.org/10.21268/20250805-0 SP - 1 EP - 3 PB - TU Clausthal-Zellerfeld CY - Clausthal-Zellerfeld ER - TY - GEN A1 - Chatharajupalli, Navya Sneha A1 - Rotta, Randolf A1 - Karnapke, Reinhardt A1 - Nolte, Jörg T1 - VibroMote : Wi-Fi-based mesh communication for railway bridge inspection and monitoring T2 - 2025 International Symposium on Networks, Computers and Communications (ISNCC) N2 - Vibration sensing provides insights into the dynamic behaviour of engineering constructions such as railway bridges. Cable-based sensors are viable only for long-term condition monitoring and rare special inspections because of the labor-intensive deployment. Although wireless sensors significantly reduce this overhead, their energy constraints limited the network throughput and, hence, their resolution in space and time. Batteryor solar-powered sensor nodes with high network throughput would enable in-depth measurements during regular inspections and improve the access to high-quality monitoring data. We present “VibroMote”, which combines energy harvesting, a high-bandwidth 3-axis MEMS accelerometer, and high-throughput, self-organizing mesh communication via IEEE 802.11 Wi-Fi. The evaluation on a real bridge with 18 VibroMotes shows that the deployment time can be reduced from hours to minutes; the multi-hop mesh provides sufficient throughput reserves for the application whereas direct one-hop communication failed; the battery runtime is sufficient for temporary measurements during inspections; and the energy consumption during sleep modes would be low enough for solar-powered long-term monitoring. Hence, the combination of high-throughput Wi-Fi with mesh networking is a strong alternative to the commonly used low-power radio technologies when long range between the sensors is not needed. KW - Wireless Mesh Network KW - Condition Monitoring KW - Multi-hop routing KW - Wi-Fi Mesh Y1 - 2025 SN - 978-1-6654-5769-9 U6 - https://doi.org/10.1109/ISNCC66965.2025.11250402 SN - 2768-0940 SP - 1 EP - 6 PB - IEEE CY - Piscataway, NJ ER -