{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T12:13:44Z","timestamp":1767183224016,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":18,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T00:00:00Z","timestamp":1666569600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"ministerio de ciencia y tecnolog\u00eda. Gobierno de Espa\u00f1a","award":["PID2020-113795RBC33\/ AEI\/10.13039\/501100011033"],"award-info":[{"award-number":["PID2020-113795RBC33\/ AEI\/10.13039\/501100011033"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,24]]},"DOI":"10.1145\/3551663.3558681","type":"proceedings-article","created":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T22:06:16Z","timestamp":1666217176000},"page":"9-16","source":"Crossref","is-referenced-by-count":8,"title":["Prototype of deployment of Federated Learning with IoT devices"],"prefix":"10.1145","author":[{"given":"Pablo","family":"Garc\u00eda Santaclara","sequence":"first","affiliation":[{"name":"University of Vigo, Vigo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ana","family":"Fern\u00e1ndez Vilas","sequence":"additional","affiliation":[{"name":"University of Vigo, Vigo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rebeca P.","family":"D\u00edaz Redondo","sequence":"additional","affiliation":[{"name":"University of Vigo, Vigo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,10,24]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"12th USENIX symposium on operating systems design and implementation. 265--283","author":"Abadi Mart\u00edn","year":"2016","unstructured":"Mart\u00edn Abadi , Paul Barham , Jianmin Chen , Zhifeng Chen , Andy Davis , Jeffrey Dean , Matthieu Devin , Sanjay Ghemawat , Geoffrey Irving , Michael Isard , 2016 . Tensorflow: A system for large-scale machine learning . In 12th USENIX symposium on operating systems design and implementation. 265--283 . Mart\u00edn Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al. 2016. Tensorflow: A system for large-scale machine learning. In 12th USENIX symposium on operating systems design and implementation. 265--283."},{"key":"e_1_3_2_1_2_1","volume-title":"Fed- erated Learning: A Survey on Enabling Technologies, Protocols, and Applications","author":"Aledhari Mohammed","year":"2020","unstructured":"Mohammed Aledhari , Rehma Razzak , Reza M. Parizi , and Fahad Saeed . 2020. Fed- erated Learning: A Survey on Enabling Technologies, Protocols, and Applications . IEEE Access 8 ( 2020 ). https:\/\/doi.org\/10.1109\/ACCESS.2020.3013541 10.1109\/ACCESS.2020.3013541 Mohammed Aledhari, Rehma Razzak, Reza M. Parizi, and Fahad Saeed. 2020. Fed- erated Learning: A Survey on Enabling Technologies, Protocols, and Applications. IEEE Access 8 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.3013541"},{"key":"e_1_3_2_1_3_1","volume-title":"Retrieved","author":"Amazon","year":"2022","unstructured":"Amazon 2022 . Amazon EC2 . Retrieved May 27, 2022 from https:\/\/aws.amazon. com\/ec2\/ Amazon 2022. Amazon EC2. Retrieved May 27, 2022 from https:\/\/aws.amazon. com\/ec2\/"},{"key":"e_1_3_2_1_4_1","volume-title":"Retrieved","author":"Core Amazon","year":"2022","unstructured":"Amazon IoT Core 2022 . IoT Core . Retrieved May 27, 2022 from https:\/\/aws. amazon.com\/es\/iot-core Amazon IoT Core 2022. IoT Core. Retrieved May 27, 2022 from https:\/\/aws. amazon.com\/es\/iot-core"},{"key":"e_1_3_2_1_5_1","unstructured":"Fran\u00e7ois Chollet. 2015. keras. https:\/\/github.com\/fchollet\/keras. Accessed:2021.  Fran\u00e7ois Chollet. 2015. keras. https:\/\/github.com\/fchollet\/keras. Accessed:2021."},{"key":"e_1_3_2_1_6_1","volume-title":"Federated Optimization: Distributed Machine Learning for On-Device Intelligence. arXiv preprint arXiv:1610.02527","author":"Konecn\u00fd Jakub","year":"2016","unstructured":"Jakub Konecn\u00fd , H. Brendan McMahan , Daniel Ramage , and Peter Richt\u00e1rik . 2016 . Federated Optimization: Distributed Machine Learning for On-Device Intelligence. arXiv preprint arXiv:1610.02527 (2016). arXiv:1610.02527 [cs.LG] Jakub Konecn\u00fd, H. Brendan McMahan, Daniel Ramage, and Peter Richt\u00e1rik. 2016. Federated Optimization: Distributed Machine Learning for On-Device Intelligence. arXiv preprint arXiv:1610.02527 (2016). arXiv:1610.02527 [cs.LG]"},{"key":"e_1_3_2_1_7_1","unstructured":"Yann LeCun and Corinna Cortes. 2010. MNIST handwritten digit database. http:\/\/yann.lecun.com\/exdb\/mnist\/. http:\/\/yann.lecun.com\/exdb\/mnist\/  Yann LeCun and Corinna Cortes. 2010. MNIST handwritten digit database. http:\/\/yann.lecun.com\/exdb\/mnist\/. http:\/\/yann.lecun.com\/exdb\/mnist\/"},{"key":"e_1_3_2_1_8_1","unstructured":"Brendan McMahan Eider Moore Daniel Ramage Seth Hampson and Blaise Aguera y Arcas. 2017. Communication-efficient learning of deep net- works from decentralized data. In Artificial Intelligence and Statistics. PMLR 1273--1282.  Brendan McMahan Eider Moore Daniel Ramage Seth Hampson and Blaise Aguera y Arcas. 2017. Communication-efficient learning of deep net- works from decentralized data. In Artificial Intelligence and Statistics. PMLR 1273--1282."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.3036952"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2019.2941458"},{"key":"e_1_3_2_1_11_1","volume-title":"Retrieved","author":"Plotly","year":"2022","unstructured":"Plotly 2022 . Collaborative data science . Retrieved May 27, 2022 from https:\/\/plot.ly Plotly 2022. Collaborative data science. Retrieved May 27, 2022 from https:\/\/plot.ly"},{"key":"e_1_3_2_1_12_1","volume-title":"Retrieved","author":"Rapsberry Pi","year":"2022","unstructured":"Rapsberry Pi 2 2022 . RPI 2 Model B . Retrieved May 27, 2022 from https:\/\/www.raspberrypi.org\/products\/raspberry-pi-2-model-b Rapsberry Pi 2 2022. RPI 2 Model B. Retrieved May 27, 2022 from https:\/\/www.raspberrypi.org\/products\/raspberry-pi-2-model-b"},{"key":"e_1_3_2_1_13_1","volume-title":"Retrieved","author":"Rapsberry Pi","year":"2022","unstructured":"Rapsberry Pi 3 2022 . RPI 3 Model B . Retrieved May 27, 2022 from https:\/\/www.raspberrypi.org\/products\/raspberry-pi-3-model-b Rapsberry Pi 3 2022. RPI 3 Model B. Retrieved May 27, 2022 from https:\/\/www.raspberrypi.org\/products\/raspberry-pi-3-model-b"},{"key":"e_1_3_2_1_14_1","first-page":"1083","article-title":"Building smart cities applications based on iot technologies: A review","volume":"62","author":"Saleem Saleem Ibraheem","year":"2020","unstructured":"Saleem Ibraheem Saleem , S Zeebaree , Diyar Qader Zeebaree , and Adnan Mohsin Abdulazeez . 2020 . Building smart cities applications based on iot technologies: A review . Technology Reports of Kansai University 62 , 3 (2020), 1083 -- 1092 . Saleem Ibraheem Saleem, S Zeebaree, Diyar Qader Zeebaree, and Adnan Mohsin Abdulazeez. 2020. Building smart cities applications based on iot technologies: A review. Technology Reports of Kansai University 62, 3 (2020), 1083--1092.","journal-title":"Technology Reports of Kansai University"},{"key":"e_1_3_2_1_15_1","volume-title":"Co-op: Cooperative machine learning from mobile devices.","author":"Wang Yushi","year":"2017","unstructured":"Yushi Wang . 2017 . Co-op: Cooperative machine learning from mobile devices. (2017). Yushi Wang. 2017. Co-op: Cooperative machine learning from mobile devices. (2017)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.2200\/S00960ED2V01Y201910AIM043"},{"key":"e_1_3_2_1_17_1","volume-title":"Federated learning with non-iid data. arXiv preprint arXiv:1806.00582","author":"Zhao Yue","year":"2018","unstructured":"Yue Zhao , Meng Li , Liangzhen Lai , Naveen Suda , Damon Civin , and Vikas Chan- dra. 2018. Federated learning with non-iid data. arXiv preprint arXiv:1806.00582 ( 2018 ). Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, and Vikas Chan- dra. 2018. Federated learning with non-iid data. arXiv preprint arXiv:1806.00582 (2018)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.001.1900103"}],"event":{"name":"MSWiM '22: Int'l ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems","sponsor":["SIGSIM ACM Special Interest Group on Simulation and Modeling"],"location":"Montreal Quebec Canada","acronym":"MSWiM '22"},"container-title":["Proceedings of the 19th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, &amp; Ubiquitous Networks on 19th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, &amp; Ubiquitous Networks"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3551663.3558681","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3551663.3558681","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:00Z","timestamp":1750182540000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3551663.3558681"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,24]]},"references-count":18,"alternative-id":["10.1145\/3551663.3558681","10.1145\/3551663"],"URL":"https:\/\/doi.org\/10.1145\/3551663.3558681","relation":{},"subject":[],"published":{"date-parts":[[2022,10,24]]}}}