{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T18:08:41Z","timestamp":1759342121814,"version":"3.41.0"},"reference-count":34,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T00:00:00Z","timestamp":1705536000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2022YFB4502001"],"award-info":[{"award-number":["2022YFB4502001"]}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"crossref","award":["62032008 and 62232012"],"award-info":[{"award-number":["62032008 and 62232012"]}],"id":[{"id":"10.13039\/501100001809","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":[[2024,3,31]]},"abstract":"<jats:p>\n            <jats:italic>Solid State Drives<\/jats:italic>\n            (SSDs) are widely used in data-intensive scenarios due to their high performance and decreasing cost. However, in shared environments, concurrent workloads can interfere with each other, leading to a violation of\n            <jats:italic>Quality of Service<\/jats:italic>\n            (QoS). While QoS mechanisms like fairness guarantees and latency constraints have been integrated into SSDs, existing transaction processing frameworks offer limited QoS guarantees and can significantly degrade overall performance in a shared environment. The reason is that the internal components of an SSD, originally designed to exploit parallelism, struggle to coordinate effectively when QoS mechanisms are applied to them.\n          <\/jats:p>\n          <jats:p>\n            This article proposes a novel\n            <jats:bold>QoS<\/jats:bold>\n            -enhanced transaction\n            <jats:bold>pro<\/jats:bold>\n            cessing framework, called QoS-pro, which enhances QoS guarantees for concurrent workloads while maintaining high parallelism for SSDs. QoS-pro achieves this by redesigning transaction processing procedures to fully exploit the parallelism of shared SSDs and enhancing QoS-oriented transaction translation and scheduling with parallelism features in mind. In terms of fairness guarantees, QoS-pro outperforms state-of-the-art methods by achieving 96% fairness improvement and 64% maximum latency reduction. QoS-pro also shows almost no loss in throughput when compared with parallelism-oriented methods. Additionally, QoS-pro triggers the fewest\n            <jats:italic>Garbage Collection<\/jats:italic>\n            (GC) operations and minimally affects concurrently running workloads during GC operations.\n          <\/jats:p>","DOI":"10.1145\/3632955","type":"journal-article","created":{"date-parts":[[2023,11,14]],"date-time":"2023-11-14T11:30:36Z","timestamp":1699961436000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["QoS-pro: A QoS-enhanced Transaction Processing Framework for Shared SSDs"],"prefix":"10.1145","volume":"21","author":[{"given":"Hao","family":"Fan","sequence":"first","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Service Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4928-2805","authenticated-orcid":false,"given":"Yiliang","family":"Ye","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Service Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4306-5280","authenticated-orcid":false,"given":"Shadi","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Inria, University of Rennes, CNRS, IRISA, Rennes, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6094-0166","authenticated-orcid":false,"given":"Zhuo","family":"Huang","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Service Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2725-9482","authenticated-orcid":false,"given":"Xingru","family":"Li","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Service Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7646-9653","authenticated-orcid":false,"given":"Weibin","family":"Xue","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Service Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8690-127X","authenticated-orcid":false,"given":"Song","family":"Wu","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Service Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0782-0450","authenticated-orcid":false,"given":"Chen","family":"Yu","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Service Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer 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