{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,21]],"date-time":"2025-09-21T07:13:54Z","timestamp":1758438834116,"version":"3.44.0"},"reference-count":48,"publisher":"Association for Computing Machinery (ACM)","issue":"3","funder":[{"DOI":"10.13039\/501100001809","name":"NSF of China","doi-asserted-by":"crossref","award":["62272253, 62272252"],"award-info":[{"award-number":["62272253, 62272252"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Archit. Code Optim."],"published-print":{"date-parts":[[2025,9,30]]},"abstract":"<jats:p>\n            <jats:italic toggle=\"yes\">Data deduplication<\/jats:italic>\n            is an effective technique for reducing redundant data storage space in various storage systems. Generally, deduplication consists of four steps: chunking, fingerprinting, fingerprint lookup, and data management. Recently,\n            <jats:italic toggle=\"yes\">Non-volatile Memory (NVM)<\/jats:italic>\n            as an emerging storage device has received widespread attention. Directly applying the deduplication technique on NVM for storage cost savings faces many challenges: (a) deduplication on NVM devices suffers from\n            <jats:italic toggle=\"yes\">computation bottleneck<\/jats:italic>\n            instead of the I\/O bottleneck faced by deduplication on traditional storage devices (such as HDD and SSD); (b) new fingerprint indexes and metadata are required to be re-designed to adapt to NVM characteristics; (c) inline deduplication on NVM is more sensitive to the latency. To solve these challenges, we propose a novel\n            <jats:bold>Samp<\/jats:bold>\n            ling prediction-based inline data\n            <jats:bold>Dedup<\/jats:bold>\n            lication method (\n            <jats:italic toggle=\"yes\">\n              <jats:bold>SampDedup<\/jats:bold>\n            <\/jats:italic>\n            ) on NVM devices. It aims to ensure high deduplication ratios while reducing computation costs and latency by optimizing\n            <jats:italic toggle=\"yes\">data chunking<\/jats:italic>\n            ,\n            <jats:italic toggle=\"yes\">fingerprinting<\/jats:italic>\n            , and\n            <jats:italic toggle=\"yes\">fingerprint lookup<\/jats:italic>\n            . (a) For\n            <jats:italic toggle=\"yes\">data chunking<\/jats:italic>\n            , a sampling prediction-based chunking method (\n            <jats:italic toggle=\"yes\">SampChunk<\/jats:italic>\n            ) is proposed to leverage chunk similarity to distinguish duplicate chunks and skip them for chunking. This method can be easily integrated into most sliding-window based and non-window based CDC chunking algorithms. (b) For\n            <jats:italic toggle=\"yes\">fingerprinting<\/jats:italic>\n            , the commonly used SHA-1 algorithm is further optimized to reduce the extra computational overhead introduced by SampChunk, and an asynchronous fingerprinting method is proposed to reduce the fingerprinting latency of unique chunks. (c) For\n            <jats:italic toggle=\"yes\">fingerprint lookup<\/jats:italic>\n            , we design a header fingerprint index and metadata table for each data chunk constructed by SampChunk on NVM, and we use a fast-read buffer to replace the traditional slow LRU cache to improve search efficiency. Experiments on four real-world datasets demonstrate that SampDedup consistently presents high inline data deduplication ratios on NVM with different workloads and data partitioning algorithms while saving more than 90% chunking time compared with state-of-the-art deduplication baselines.\n          <\/jats:p>","DOI":"10.1145\/3750447","type":"journal-article","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T11:14:11Z","timestamp":1753269251000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["SampDedup: Sampling Prediction for Efficient Inline Data Deduplication on Non-volatile Memory"],"prefix":"10.1145","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-5171-2794","authenticated-orcid":false,"given":"Ziyue","family":"Xu","sequence":"first","affiliation":[{"name":"Nankai University","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9167-5746","authenticated-orcid":false,"given":"Yichen","family":"Li","sequence":"additional","affiliation":[{"name":"Nankai University","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5631-7415","authenticated-orcid":false,"given":"Ranzhe","family":"Deng","sequence":"additional","affiliation":[{"name":"Nankai University","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6236-3673","authenticated-orcid":false,"given":"Liping","family":"Yi","sequence":"additional","affiliation":[{"name":"Nankai University","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6623-350X","authenticated-orcid":false,"given":"Yusen","family":"Li","sequence":"additional","affiliation":[{"name":"Computer Science, Nankai University","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0387-2501","authenticated-orcid":false,"given":"Gang","family":"Wang","sequence":"additional","affiliation":[{"name":"Computer Science, Nankai University","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9010-3278","authenticated-orcid":false,"given":"Xiaoguang","family":"Liu","sequence":"additional","affiliation":[{"name":"Computer Science, Nankai University","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,9,19]]},"reference":[{"key":"e_1_3_1_2_2","first-page":"419","volume-title":"NSDI","author":"Agarwal Bhavish","year":"2010","unstructured":"Bhavish Agarwal, Aditya Akella, Ashok Anand, Athula Balachandran, Pushkar Chitnis, Chitra Muthukrishnan, Ramachandran Ramjee, and George Varghese. 2010. 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USENIX Association, Denver, CO, United states, 101\u2013114."},{"key":"e_1_3_1_44_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2020.2984632"},{"key":"e_1_3_1_45_2","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA.2015.7056056"},{"key":"e_1_3_1_46_2","doi-asserted-by":"publisher","DOI":"10.5555\/3386691.3386708"},{"key":"e_1_3_1_47_2","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2015.7218510"},{"key":"e_1_3_1_48_2","first-page":"269","volume-title":"Fast","author":"Zhu Benjamin","year":"2008","unstructured":"Benjamin Zhu, Kai Li, and R. Hugo Patterson. 2008. Avoiding the disk bottleneck in the data domain deduplication file system. In Fast, Vol. 8. 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