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To address these issues, we propose an energy-efficient personalized federated search framework. This framework has three key components. Firstly, we search for partial models with high inference efficiency to reduce training energy consumption and the occurrence of stragglers in each round. Secondly, we build lightweight search controllers that control the model sampling and respond to runtime variances, mitigating new straggler issues caused by co-running applications. Finally, we design an adaptive search update strategy based on graph aggregation to improve personalized training convergence. Our framework reduces the energy consumption of the training process by lowering the training overhead of each round and speeding up the training convergence rate. Experimental results show that our approach achieves up to 5.02% accuracy and 3.45\u00d7 energy efficiency improvements.<\/jats:p>","DOI":"10.1145\/3609435","type":"journal-article","created":{"date-parts":[[2023,9,9]],"date-time":"2023-09-09T13:33:18Z","timestamp":1694266398000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Energy-efficient Personalized Federated Search with Graph for Edge Computing"],"prefix":"10.1145","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9525-2096","authenticated-orcid":false,"given":"Zhao","family":"Yang","sequence":"first","affiliation":[{"name":"College of Future Transportation, Chang\u2019an University, China and School of Computer Science, Northwestern Polytechnical University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6869-3566","authenticated-orcid":false,"given":"Qingshuang","family":"Sun","sequence":"additional","affiliation":[{"name":"Faculty of Science and Bio-Engineering Sciences, Vrije Universiteit Brussel, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,9,9]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"Monsoon. 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