Harillo, E. C., & Freitag, F. (2022). LoRaCoin: Towards a blockchain-based platform for managing LoRa devices. 1-2. https://doi.org/10.1109/INFOCOMWKSHPS54753.2022.9798276

Llisterri-Giménez, N., Monfort_Grau, M., Pueyo, R. C., & Freitag, F. (2022). On-Device Training of Machine Learning Models on Microcontrollers with Federated Learning. Electronics, 11. https://doi.org/10.3390/electronics11040573 (Original work published 2022)

Freitag, F., Vilchez, P., Wei, L., Liu, C.-H., & Selimi, M. (2022). Performance Evaluation of Federated Learning Over Wireless Mesh Networks with Low-Capacity Devices. online: Springer International Publishing.

Del Solar, A. J. C., Solé, J. M., & Freitag, F. (2022). Towards a Monitoring System for a LoRa Mesh Network. Presented at the. https://doi.org/10.1109/ICDCS54860.2022.00139

Pueyo, R. C., Freitag, F., Meseguer, R., & Navarro, L. (2021). A minimalistic distance-vector routing protocol for LoRa mesh networks. Retrieved from http://hdl.handle.net/2117/347444 (Original work published 2026)

Panadero, J., Selimi, M., Calvet, L., Marquès, J. M., & Freitag, F. (2021). A two-stage Multi-Criteria Optimization method for service placement in decentralized edge micro-clouds. Future Generation Computer Systems, Future Generation Computer Systems. https://doi.org/https://doi.org/10.1016/j.future.2021.03.013 (Original work published 1021)

Pueyo, R. C. (2021). Towards LoRa mesh networks for the IoT. https://doi.org/10.5821/dissertation-2117-360904

Semlali, B.-E. B., & Freitag, F. (2021). SAT-Hadoop-Processor: A Distributed Remote Sensing Big Data Processing Software for Earth Observation Applications. Applied Sciences, 11. https://doi.org/10.3390/app112210610 (Original work published 2021)

Freitag, F., Vilchez, P., Wei, L., Liu, C.-H., & Selimi, M. (2021). Poster: Testbed in Wireless City Mesh Network with Application to Federated Learning Experiments. Retrieved from https://my.ece.msstate.edu/faculty/chliu/papers/conference/PosterFL_IoT… (Original work published 2021)

Grau, M. M., Pueyo, R. C., & Freitag, F. (2021). On-Device Training of Machine Learning Models on Microcontrollers With a Look at Federated Learning. 198–203. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3462203.3475896

Pueyo, R. C., Meseguer, R., Freitag, F., Navarro, L., Ochoa, S. F., & Santos, R. M. (2021). LoRaMoto: A communication system to provide safety awareness among civilians after an earthquake. Future Generation Computer Systems, 115, 150–170. https://doi.org/10.1016/j.future.2020.07.040 (Original work published 2021)

Navarro, L., Cano, J., Manco-Sanchez, A., Franquesa, D., Vilchez, P., Freitag, F., … Lembke, R. S. (2021). Decentralized data ecosystem for the Open Blockchain for Asset Disposition Alliance Deliverable 3: Experiment Results and Final Report. Barcelona. Retrieved from https://people.ac.upc.edu/leandro/p/D3-final-pub.pdf (Original work published 2021)

Pueyo, R. C., Freitag, F., Meseguer, R., & Navarro, L. (2021). Beyond the Star of Stars: An Introduction to Multihop and Mesh for LoRa and LoRaWAN. IEEE Pervasive Computing, 20, 63-72. https://doi.org/10.1109/MPRV.2021.3063443

Ibraimi, L., Selimi, M., & Freitag, F. (2021). BePOCH: Improving Federated Learning Performance in Resource-Constrained Computing Devices. Presented at the. Madrid: IEEE. https://doi.org/10.1109/GLOBECOM46510.2021.9685095 (Original work published 2021)

Dimogerontakis, E., Navarro, L., Selimi, M., Mosquera, S., & Freitag, F. (2020). Contract networking for crowdsourced connectivity. Presented at the. Oxford, UK: IEEE. Retrieved from http://people.ac.upc.edu/leandro/pubs/meshdapp20.pdf

Pueyo, R. C., Selimi, M., Freitag, F., & Navarro, L. (2020). A Monitoring System for Distributed Edge Infrastructures with Decentralized Coordination (I. Brandic, T. A. L. Genez, I. Pietri, & R. Sakellariou, Eds.). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-58628-710.1007/978-3-030-58628-7_4

Tous, R., & Freitag, F. (2020). Open project-based learning for dynamic adaptability of IT education. The International Journal of Electrical Engineering & Education. https://doi.org/10.1177/0020720920981535

Pueyo, R. C., Selimi, M., Freitag, F., & Navarro, L. (2020). REDEMON: Resilient Decentralized Monitoring System for Edge Infrastructures. Presented at the. Melbourne, Australia: IEEE. https://doi.org/10.1109/CCGrid49817.202010.1109/CCGrid49817.2020.00-84

Selimi, M., Navarro, L., Braem, B., Freitag, F., & Lertsinsrubtavee, A. (2020). Towards Information-Centric Edge Platform for Mesh Networks: The Case of CityLab Testbed. Presented at the. (Original work published 2020)

Pueyo, R. C., Freitag, F., Meseguer, R., Navarro, L., Ochoa, S. F., & Santos, R. M. (2019). A LoRa-Based Communication System for Coordinated Response in an Earthquake Aftermath. Proceedings, 31, 73. https://doi.org/10.3390/proceedings2019031073 (Original work published 2019)

Apolónia, N., Freitag, F., Navarro, L., & Girdzijauskas, S. (2019). Socially aware microcloud service overlay optimization in community networks. https://doi.org/10.1002/spe.2750 (Original work published 2019)

Dimogerontakis, E., Navarro, L., Selimi, M., Mosquera, S., & Freitag, F. (2019). MeshDapp - Blockchain-enabled Sustainable Business Models for Networks. Presented at the. Leeds: Springer LNCS Proceedings. Retrieved from http://people.ac.upc.edu/leandro/pubs/Gecon19-meshdapp-short.pdf (Original work published 2019)

Selimi, M., Cerdà-Alabern, L., Freitag, F., Veiga, L., Sathiaseelan, A., & Crowcroft, J. (2019). A lightweight service placement approach for community network micro-clouds. Journal of Grid Computing, 17, 169–189. Retrieved from https://link.springer.com/article/10.1007/s10723-018-9437-3

Freitag, F., Navarro, L., Selimi, M., & Pueyo, R. C. (2019). End User-Managed Service Deployments in Microclouds at the Network Edge. Presented at the. Osaka, Japan: IEEE. https://doi.org/10.1109/GCCE46687.201910.1109/GCCE46687.2019.9015407

San Miguel, E., Timmerman, R., Mosquera, S., Dimogerontakis, E., Freitag, F., & Navarro, L. (2019). Blockchain-Enabled Participatory Incentives for Crowdsourced Mesh Networks. Presented at the. Leeds: Springer LNCS Proceedings. Retrieved from http://people.ac.upc.edu/leandro/pubs/gecon19-ds-incent.pdf (Original work published 2019)