{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:44:24Z","timestamp":1767321864498,"version":"3.48.0"},"publisher-location":"Singapore","reference-count":15,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819541577","type":"print"},{"value":"9789819541584","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-4158-4_28","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:40:09Z","timestamp":1767321609000},"page":"394-407","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["OLearning: A Geo-Distributed System for\u00a0Device-Cloud Collaborative Computing"],"prefix":"10.1007","author":[{"given":"Min","family":"Fang","sequence":"first","affiliation":[]},{"given":"Zhihui","family":"Fu","sequence":"additional","affiliation":[]},{"given":"Xiangmou","family":"Qu","sequence":"additional","affiliation":[]},{"given":"Ruiguang","family":"Pei","sequence":"additional","affiliation":[]},{"given":"Jun","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Lan","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"28_CR1","first-page":"374","volume":"1","author":"K Bonawitz","year":"2019","unstructured":"Bonawitz, K., Eichner, H., et al.: Towards federated learning at scale: system design. Proc. Mach. Learn. Syst. 1, 374\u2013388 (2019)","journal-title":"Proc. Mach. Learn. Syst."},{"key":"28_CR2","unstructured":"Paulik, M., Seigel, M., Mason, H., et\u00a0al.: Federated evaluation and tuning for on-device personalization: System design & applications. arXiv:2102.08503 (2021)"},{"key":"28_CR3","unstructured":"Lai, F., Zhu, X., Madhyastha, H.V., Chowdhury, M.: Oort: efficient federated learning via guided participant selection. In: OSDI, pp. 19\u201335 (2021)"},{"key":"28_CR4","doi-asserted-by":"crossref","unstructured":"Li, C., Zeng, X., Zhang, M., Cao, Z.: Pyramidfl: a fine-grained client selection framework for efficient federated learning. In: MobiCom, pp. 158\u2013171 (2022)","DOI":"10.1145\/3495243.3517017"},{"key":"28_CR5","unstructured":"McMahan, B., et\u00a0al.: Communication-efficient learning of deep networks from decentralized data. In: Artificial Intelligence and Statistics, pp. 1273\u20131282 (2017)"},{"key":"28_CR6","unstructured":"Next-Gen Cloud Services for LLMs & Generative AI (2023). https:\/\/fedml.ai\/"},{"key":"28_CR7","unstructured":"Flower: A Friendly Federated Learning Framework (2023). https:\/\/flower.dev\/"},{"issue":"4","key":"28_CR8","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1016\/0166-218X(81)90005-6","volume":"3","author":"S Martello","year":"1981","unstructured":"Martello, S., Toth, P.: A bound and bound algorithm for the zero-one multiple knapsack problem. Disc. Appl. Math. 3(4), 275\u2013288 (1981)","journal-title":"Disc. Appl. Math."},{"key":"28_CR9","unstructured":"Google: OR-Tools (2024). https:\/\/developers.google.com\/optimization\/pack"},{"issue":"2","key":"28_CR10","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1145\/214392.214397","volume":"11","author":"S Martello","year":"1985","unstructured":"Martello, S., Toth, P.: Algorithm 632: a program for the 0\u20131 multiple knapsack problem. ACM Trans. Math. Softw. 11(2), 135\u2013140 (1985)","journal-title":"ACM Trans. Math. Softw."},{"key":"28_CR11","doi-asserted-by":"crossref","unstructured":"Karger, D., et\u00a0al.: Consistent hashing and random trees: distributed caching protocols for relieving hot spots on the world wide web. In: STOC, pp. 654\u2013663 (1997)","DOI":"10.1145\/258533.258660"},{"key":"28_CR12","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"28_CR13","unstructured":"Reddi, S., et al.: Adaptive federated optimization. arXiv:2003.00295 (2020)"},{"key":"28_CR14","first-page":"429","volume":"2","author":"T Li","year":"2020","unstructured":"Li, T., Sahu, A.K., Zaheer, M., et al.: Federated optimization in heterogeneous networks. Proc. Mach. Learn. Syst. 2, 429\u2013450 (2020)","journal-title":"Proc. Mach. Learn. Syst."},{"key":"28_CR15","unstructured":"Schuster, T., et al.: Confident adaptive language modeling. In: NeurIPS, vol. 35, pp. 17456\u201317472 (2022)"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-4158-4_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:40:11Z","timestamp":1767321611000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-4158-4_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819541577","9789819541584"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-4158-4_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 May 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 May 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/dasfaa2025.github.io","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}