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However, many deep learning-based MTS anomaly detection models require long-term MTS training data to achieve optimal performance, which often conflicts with the frequent pattern changes observed in software systems. Moreover, the training overhead of vast MTS in large-scale software systems is unacceptably high. To address these issues, we design\n            <jats:italic>OmniTransfer<\/jats:italic>\n            , a model-agnostic framework that combines weighted hierarchical agglomerative clustering with an adaptive transfer learning strategy, making many state-of-the-art (SOTA) MTS anomaly detection models efficient and effective. Extensive experiments using real-world data from a large web content service provider and a network operator show that\n            <jats:italic>OmniTransfer<\/jats:italic>\n            significantly reduces the model initialization time by 46.49% and the training cost by 74.51%, while maintaining high accuracy in detecting anomalies.\n          <\/jats:p>","DOI":"10.1145\/3702984","type":"journal-article","created":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T15:13:01Z","timestamp":1730733181000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Efficient Multivariate Time Series Anomaly Detection through Transfer Learning for Large-Scale Software Systems"],"prefix":"10.1145","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0266-7899","authenticated-orcid":false,"given":"Yongqian","family":"Sun","sequence":"first","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8481-2599","authenticated-orcid":false,"given":"Minghan","family":"Liang","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0330-0028","authenticated-orcid":false,"given":"Shenglin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9369-7592","authenticated-orcid":false,"given":"Zeyu","family":"Che","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9663-6647","authenticated-orcid":false,"given":"Zhiyao","family":"Luo","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7423-0964","authenticated-orcid":false,"given":"Dongwen","family":"Li","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6729-925X","authenticated-orcid":false,"given":"Yuzhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5113-838X","authenticated-orcid":false,"given":"Dan","family":"Pei","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4261-2467","authenticated-orcid":false,"given":"Lemeng","family":"Pan","sequence":"additional","affiliation":[{"name":"Huawei Technologies Co., Ltd, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4984-3290","authenticated-orcid":false,"given":"Liping","family":"Hou","sequence":"additional","affiliation":[{"name":"Huawei Technologies Co., Ltd, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,4,26]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"Minghan Liang Zeyu Che and Zhiyao Luo. 2024. 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