{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T14:49:58Z","timestamp":1776350998515,"version":"3.51.2"},"reference-count":31,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T00:00:00Z","timestamp":1618963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62072214 and 61572232"],"award-info":[{"award-number":["62072214 and 61572232"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"International Cooperation Project of Guangdong Province","award":["2020A0505100040"],"award-info":[{"award-number":["2020A0505100040"]}]},{"name":"Open Research Fund of Key Laboratory of Computer System and Architecture"},{"name":"Institute of Computing Technology"},{"DOI":"10.13039\/501100002367","name":"Chinese Academy of Sciences","doi-asserted-by":"crossref","award":["CARCH201705"],"award-info":[{"award-number":["CARCH201705"]}],"id":[{"id":"10.13039\/501100002367","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM\/IMS Trans. Data Sci."],"published-print":{"date-parts":[[2021,5,31]]},"abstract":"<jats:p>Restoring data is the main purpose of data backup in storage systems. The fragmentation issue, caused by physically scattering logically continuous data across a variety of disk locations, poses a negative impact on the restoring performance of a deduplication system. Rewriting algorithms are used to alleviate the fragmentation problem by improving the restoring speed of a deduplication system. However, rewriting methods give birth to a big sacrifice in terms of deduplication ratio, leading to a huge storage space waste. Furthermore, traditional backup approaches treat file metadata and chunk metadata as the same, which causes frequent on-disk metadata accesses.<\/jats:p>\n                  <jats:p>\n                    In this article, we start by analyzing storage characteristics of backup metadata. An intriguing finding shows that with 10 million files, the file metadata merely takes up approximately 340 MB. Motivated by this finding, we propose a Classified-Metadata based Restoring method (CMR) that classifies backup metadata into\n                    <jats:italic toggle=\"yes\">file metadata<\/jats:italic>\n                    and\n                    <jats:italic toggle=\"yes\">chunk metadata<\/jats:italic>\n                    . Because the\n                    <jats:italic toggle=\"yes\">file metadata<\/jats:italic>\n                    merely takes up a meager amount of space, CMR maintains all file metadata in memory, whereas chunk metadata are aggressively prefetched to memory in a greedy manner. A deduplication system with CMR in place exhibits three salient features: (i) It avoids rewriting algorithms\u2019 additional overhead by reducing the number of disk reads in a restoring process, (ii) it increases the restoring throughput without sacrificing the deduplication ratio, and (iii) it thoroughly leverages the hardware resources to boost the restoring performance. To quantitatively evaluate the performance of CMR, we compare our CMR against two state-of-the-art approaches, namely, a history-aware rewriting method (HAR) and a context-based rewriting scheme (CAP). The experimental results show that compared to HAR and CAP, CMR reduces the restoring time by 27.2% and 29.3%, respectively. Moreover, the deduplication ratio is improved by 1.91% and 4.36%, respectively.\n                  <\/jats:p>","DOI":"10.1145\/3437261","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T16:05:51Z","timestamp":1619021151000},"page":"1-16","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Boosting the Restoring Performance of Deduplication Data by Classifying Backup Metadata"],"prefix":"10.1145","volume":"2","author":[{"given":"Ru","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Computer Science, Jinan University, P. R.China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhui","family":"Deng","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jinan University, State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, P. 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