{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T08:12:00Z","timestamp":1778227920313,"version":"3.51.4"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819203659","type":"print"},{"value":"9789819203666","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\/978-981-92-0366-6_13","type":"book-chapter","created":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T07:28:47Z","timestamp":1778225327000},"page":"199-215","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards Real-Time Maintenance of\u00a0HNSW for\u00a0ANN Search on\u00a0Edge Devices"],"prefix":"10.1007","author":[{"given":"Wenbo","family":"Zhao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuheng","family":"Chang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangtao","family":"Cui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,5,9]]},"reference":[{"key":"13_CR1","unstructured":"Han, S., Mao, H., Dally, W.J.: Deep compression: compressing deep neural networks with pruning, trained quantization and Huffman coding. In: Proceedings of ICLR \u201916 (2016)"},{"key":"13_CR2","doi-asserted-by":"crossref","unstructured":"Howard, A., Sandler, M., Chu, G., Chen, L.-C., Chen, B., et\u00a0al.: Searching for MobileNetV3. In: Proceedings of IEEE\/CVF ICCV \u201919, pp. 1314\u20131324 (2019)","DOI":"10.1109\/ICCV.2019.00140"},{"key":"13_CR3","doi-asserted-by":"crossref","unstructured":"Fan, W., Ding, Y., Ning, L., Wang, S., et\u00a0al.: A survey on rag meeting LLMs: towards retrieval-augmented large language models. In: Proceedings of ACM SIGKDD \u201924, pp. 6491\u20136501 (2024)","DOI":"10.1145\/3637528.3671470"},{"key":"13_CR4","unstructured":"Park, T., Lee, G., Kim. , M.-S.: MobileRAG: a fast, memory-efficient, and energy-efficient method for on-device RAG. arXiv preprint arXiv:2507.01079v1 (2025)"},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Chen, K., Xiao, J., Liu, J., Tong, Q., et\u00a0al.: Semantic visual simultaneous localization and mapping: a survey. IEEE Trans. Intell. Transp. Syst. (2025)","DOI":"10.1109\/TITS.2025.3556928"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Malkov, Y.A., Yashunin, D.A.: Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE Trans. Pattern Anal. Mach. Intell. 42(4), 824\u2013836 (2018)","DOI":"10.1109\/TPAMI.2018.2889473"},{"issue":"3","key":"13_CR7","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1109\/TBDATA.2019.2921572","volume":"7","author":"J Johnson","year":"2019","unstructured":"Johnson, J., Douze, M., J\u00e9gou, H.: Billion-scale similarity search with GPUs. IEEE Trans. Big Data 7(3), 535\u2013547 (2019)","journal-title":"IEEE Trans. Big Data"},{"key":"13_CR8","unstructured":"Yao, J., Zhang, S., Yao, Y., Wang, F., Ma, J., et\u00a0al.: Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI. IEEE Trans. Knowl. Data Eng. 35(7), 6866\u20136886 (2023)"},{"key":"13_CR9","unstructured":"Subramanya, S.J., Devvrit, F., Simhadri, H.V., Krishnawamy, R., Kadekodi, R.: DiskANN: fast accurate billion-point nearest neighbor search on a single node. Adv. Neural. Inf. Process. Syst. 32, 13766\u201313776 (2019)"},{"key":"13_CR10","unstructured":"Singh, A., Subramanya, S.J., Krishnaswamy, R., Simhadri, H.V.: FreshDiskANN: a Fast and accurate graph-based ANN index for streaming similarity search. arXiv preprint arXiv:2105.09613 (2021)"},{"key":"13_CR11","unstructured":"Xu, H., Manohar, M.D., Bernstein, P.A., Chandramouli, B., Wen, R., et\u00a0al.: In-place updates of a graph index for streaming approximate nearest neighbor search. arXiv preprint arXiv:2502.13826 (2025)"},{"key":"13_CR12","unstructured":"Yu, S., Lin, S., Gong, S., Xie, Y., et\u00a0al.: A topology-aware localized update strategy for graph-based ANN index. In: Proceedings of VLDB \u201926 (2026)"},{"key":"13_CR13","doi-asserted-by":"publisher","unstructured":"Xiao, W., Zhan, Y., Xi, R., Hou, Z., Liao, J., Sun, Y.: Mint: an efficient and robust in-place update approach for graph-based vector index. In Wu, X., et\u00a0al. Data Science: Foundations and Applications. PAKDD 2025. LNCS, vol. 15876, pp. 78\u201390. Springer, Singapore (2025). https:\/\/doi.org\/10.1007\/978-981-96-8298-0_7","DOI":"10.1007\/978-981-96-8298-0_7"},{"key":"13_CR14","unstructured":"Jin, H., Lee, J., Piao, S., Seo, S., Park, S.: PRO-HNSW: proactive repair and optimization for high-performance dynamic HNSW indexes. In: Proceedings of IEEE ICDE \u201926 (2026)"},{"key":"13_CR15","unstructured":"Xu, Z., Zhao, W., Tan, S., Zhou, Z., Li, P.: Proximity graph maintenance for fast online nearest neighbor search. arXiv preprint arXiv:2206.10839 (2022)"},{"key":"13_CR16","unstructured":"Zhang, Z., Wei, Y., Engels, J., Shun, J.: CleANN: efficient full dynamism in graph-based approximate nearest neighbor search. arXiv preprint arXiv:2507.19802 (2025)"},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"J\u00e9gou, H., Douze, M., Schmid, C.: Product quantization for nearest neighbor search. IEEE Trans. Pattern Anal. Mach. Intell. 33(1), 117\u2013128 (2011)","DOI":"10.1109\/TPAMI.2010.57"},{"key":"13_CR18","unstructured":"Gionis, A., Indyk, P., Motwani, R.: Similarity search in high dimensions via hashing. In: Proceedings of the VLDB \u201999, pp. 518\u2013529 (1999)"},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"Fu, C., Xiang, C., Wang, C., Cai, D.: Fast approximate nearest neighbor search with the navigating spreading-out graph. Proc. VLDB Endow. 12(5), 461\u2013474 (2019)","DOI":"10.14778\/3303753.3303754"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Li, W., Zhang, Y., Sun, Y., et\u00a0al.: Approximate nearest neighbor search on high dimensional data - experiments, analyses, and improvement. IEEE Trans. Knowl. Data Eng. 32(8), 1475\u20131488 (2020)","DOI":"10.1109\/TKDE.2019.2909204"},{"issue":"8","key":"13_CR21","first-page":"4139","volume":"44","author":"F Cong","year":"2022","unstructured":"Cong, F., Wang, C., Cai, D.: High dimensional similarity search with satellite system graph: efficiency, scalability, and unindexed query compatibility. IEEE Trans. Pattern Anal. Mach. Intell. 44(8), 4139\u20134150 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"13_CR22","doi-asserted-by":"publisher","first-page":"106970","DOI":"10.1016\/j.patcog.2019.106970","volume":"96","author":"JV Mu\u00f1oz","year":"2019","unstructured":"Mu\u00f1oz, J.V., Gon\u00e7alves, M.A., Dias, Z., Torres, R.S.: Hierarchical clustering-based graphs for large scale approximate nearest neighbor search. Pattern Recogn. 96, 106970 (2019)","journal-title":"Pattern Recogn."},{"key":"13_CR23","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L.: ImageNet: a large-scale hierarchical image database. In: Proceedings of IEEE CVPR \u201909, pp. 248\u2013255 (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"13_CR24","unstructured":"hnswlib. https:\/\/github.com\/nmslib\/hnswlib"}],"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\/978-981-92-0366-6_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T07:29:07Z","timestamp":1778225347000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-0366-6_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819203659","9789819203666"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-0366-6_13","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":"9 May 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"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":"Jeju","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 April 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 April 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/dasfaa2026.github.io\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}