{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T16:36:28Z","timestamp":1772642188847,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T00:00:00Z","timestamp":1705968000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Minister of Science and Technology, Taiwan","award":["MOST 111-2221-E-002-134-MY3"],"award-info":[{"award-number":["MOST 111-2221-E-002-134-MY3"]}]},{"name":"Minister of Science and Technology, Taiwan","award":["NTU-112L900902"],"award-info":[{"award-number":["NTU-112L900902"]}]},{"name":"Minister of Science and Technology, Taiwan","award":["TSMC 112H1002-D"],"award-info":[{"award-number":["TSMC 112H1002-D"]}]},{"name":"National Taiwan University","award":["MOST 111-2221-E-002-134-MY3"],"award-info":[{"award-number":["MOST 111-2221-E-002-134-MY3"]}]},{"name":"National Taiwan University","award":["NTU-112L900902"],"award-info":[{"award-number":["NTU-112L900902"]}]},{"name":"National Taiwan University","award":["TSMC 112H1002-D"],"award-info":[{"award-number":["TSMC 112H1002-D"]}]},{"name":"Taiwan Semiconductor Manufacturing","award":["MOST 111-2221-E-002-134-MY3"],"award-info":[{"award-number":["MOST 111-2221-E-002-134-MY3"]}]},{"name":"Taiwan Semiconductor Manufacturing","award":["NTU-112L900902"],"award-info":[{"award-number":["NTU-112L900902"]}]},{"name":"Taiwan Semiconductor Manufacturing","award":["TSMC 112H1002-D"],"award-info":[{"award-number":["TSMC 112H1002-D"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>In this study, we present a federated learning approach that combines a multi-branch network and the Oort client selection algorithm to improve the performance of federated learning systems. This method successfully addresses the significant issue of non-iid data, a challenge not adequately tackled by the commonly used MFedAvg method. Additionally, one of the key innovations of this research is the introduction of uniformity, a metric that quantifies the disparity in training time amongst participants in a federated learning setup. This novel concept not only aids in identifying stragglers but also provides valuable insights into assessing the fairness and efficiency of the system. The experimental results underscore the merits of the integrated multi-branch network with the Oort client selection algorithm and highlight the crucial role of uniformity in designing and evaluating federated learning systems.<\/jats:p>","DOI":"10.3390\/a17020052","type":"journal-article","created":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T08:28:28Z","timestamp":1705998508000},"page":"52","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Enhancing Communication Efficiency and Training Time Uniformity in Federated Learning through Multi-Branch Networks and the Oort Algorithm"],"prefix":"10.3390","volume":"17","author":[{"given":"Pin-Hung","family":"Juan","sequence":"first","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3631-1551","authenticated-orcid":false,"given":"Ja-Ling","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106, Taiwan"},{"name":"Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei 106, Taiwan"},{"name":"Center for Data Intelligence: Technologies, Applications, and Systems, National Taiwan University, Taipei 106, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,23]]},"reference":[{"key":"ref_1","unstructured":"McMahan, B., Moore, E., Ramage, D., Hampson, S., and Arcas, B.A. (2017, January 20\u201322). 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