{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T12:08:37Z","timestamp":1763467717311,"version":"3.41.0"},"reference-count":34,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2005,11,1]],"date-time":"2005-11-01T00:00:00Z","timestamp":1130803200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Storage"],"published-print":{"date-parts":[[2005,11]]},"abstract":"<jats:p>\n            Ensuring performance isolation and differentiation among workloads that share a storage infrastructure is a basic requirement in consolidated data centers. Existing management tools rely on resource provisioning to meet performance goals; they require detailed knowledge of the system characteristics and the workloads. Provisioning is inherently slow to react to system and workload dynamics and, in the general case, it is not practical to provision for the worst case.We propose a software-only solution that ensures predictable performance for storage access. It is applicable to a wide range of storage systems and makes no assumptions about workload characteristics. We use an online feedback loop with an adaptive controller that throttles storage access requests to ensure that the available system throughput is shared among workloads according to their performance goals and their relative importance. The controller considers the system as a \u201cblack box\u201d and adapts automatically to system and workload changes. The controller is distributed to ensure high availability under overload conditions, and it can be used for both block and file access protocols. The evaluation of\n            <jats:italic>Triage<\/jats:italic>\n            , our experimental prototype, demonstrates workload isolation and differentiation in an overloaded cluster file-system where workloads and system components are changing.\n          <\/jats:p>","DOI":"10.1145\/1111609.1111612","type":"journal-article","created":{"date-parts":[[2006,2,6]],"date-time":"2006-02-06T15:07:09Z","timestamp":1139238429000},"page":"457-480","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":71,"title":["Triage"],"prefix":"10.1145","volume":"1","author":[{"given":"Magnus","family":"Karlsson","sequence":"first","affiliation":[{"name":"HP Labs, Palo Alto, CA"}]},{"given":"Christos","family":"Karamanolis","sequence":"additional","affiliation":[{"name":"HP Labs, Palo Alto, CA"}]},{"given":"Xiaoyun","family":"Zhu","sequence":"additional","affiliation":[{"name":"HP Labs, Palo Alto, CA"}]}],"member":"320","published-online":{"date-parts":[[2005,11]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/71.980028"},{"key":"e_1_2_1_2_1","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1109\/TC.2003.1197134","article-title":"User-level QoS-adaptive resource management in server end-systems","volume":"52","author":"Abdelzaher T.","year":"2003","journal-title":"IEEE Trans. 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