{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T03:12:49Z","timestamp":1774926769749,"version":"3.50.1"},"reference-count":126,"publisher":"Association for Computing Machinery (ACM)","issue":"4","funder":[{"name":"National Science Foundation","award":["2122155 and 2239291"],"award-info":[{"award-number":["2122155 and 2239291"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Comput. Syst."],"published-print":{"date-parts":[[2025,11,30]]},"abstract":"<jats:p>\n                    Trace replay is a common approach for evaluating systems by rerunning historical traffic patterns, but it\u2019s not always possible to find suitable real-world traces at the desired level of system load. To experiment with different loads, one needs to\n                    <jats:italic toggle=\"yes\">downscale<\/jats:italic>\n                    a trace to decrease the load or\n                    <jats:italic toggle=\"yes\">upscale<\/jats:italic>\n                    a trace to artificially increase the load. This article expands upon our work,\n                    <jats:italic toggle=\"yes\">TraceUpscaler<\/jats:italic>\n                    [\n                    <jats:xref ref-type=\"bibr\">92<\/jats:xref>\n                    ], by considering the interaction of upscaling and downscaling. In addition to evaluating upscaling with traces collected from a subset of the cluster, we also evaluate upscaling with traces that were downscaled with the state-of-the-art downscaling tool,\n                    <jats:italic toggle=\"yes\">TraceSplitter<\/jats:italic>\n                    [\n                    <jats:xref ref-type=\"bibr\">91<\/jats:xref>\n                    ], to demonstrate that the upscaling and downscaling techniques are compatible and do not introduce unexpected artifacts in the scaling. In addition to comparing against prior approaches, we develop a novel upscaling technique,\n                    <jats:italic toggle=\"yes\">TraceOverlap<\/jats:italic>\n                    , based on the idea of overlapping different time periods in a trace, where we identify the most similar time periods to overlap. Our evaluation demonstrates that\n                    <jats:italic toggle=\"yes\">TraceUpscaler<\/jats:italic>\n                    and\n                    <jats:italic toggle=\"yes\">TraceOverlap<\/jats:italic>\n                    are both more accurate in maintaining latency characteristics than prior approaches, with\n                    <jats:italic toggle=\"yes\">TraceUpscaler<\/jats:italic>\n                    matching the original trace latency more closely. Finally, we provide a unified framework,\n                    <jats:italic toggle=\"yes\">TraceScaler<\/jats:italic>\n                    , that combines\n                    <jats:italic toggle=\"yes\">TraceUpscaler<\/jats:italic>\n                    with\n                    <jats:italic toggle=\"yes\">TraceSplitter<\/jats:italic>\n                    to provide experimenters a common tool for their trace scaling needs.\n                  <\/jats:p>","DOI":"10.1145\/3760774","type":"journal-article","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T11:26:51Z","timestamp":1755516411000},"page":"1-31","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["TraceScaler: A Framework for Scaling Load in Real-World Traces for System Evaluation"],"prefix":"10.1145","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-3486-8542","authenticated-orcid":false,"given":"Sultan Mahmud","family":"Sajal","sequence":"first","affiliation":[{"name":"Computer Science and Engineering, The Pennsylvania State University","place":["University Park, United States"]},{"name":"Meta Platforms Inc","place":["University Park, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0060-0885","authenticated-orcid":false,"given":"Md Salman","family":"Estyak","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, The Pennsylvania State University","place":["University Park, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4469-8545","authenticated-orcid":false,"given":"Rubaba","family":"Hasan","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, The Pennsylvania State University","place":["University Park, United States"]},{"name":"Mathematics & Computer Science, Saint Mary's College of California","place":["University Park, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8394-8953","authenticated-orcid":false,"given":"Timothy","family":"Zhu","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, The Pennsylvania State University","place":["University Park, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3495-6345","authenticated-orcid":false,"given":"Bhuvan","family":"Urgaonkar","sequence":"additional","affiliation":[{"name":"The Pennsylvania State University","place":["University Park, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4272-3293","authenticated-orcid":false,"given":"Siddhartha","family":"Sen","sequence":"additional","affiliation":[{"name":"Microsoft Research New York City","place":["New York, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,11,6]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1145\/3383669.3398276","volume-title":"Proceedings of the 13th ACM International Systems and Storage Conference","author":"Akgun Ibrahim Umit","year":"2020","unstructured":"Ibrahim Umit Akgun, Geoff Kuenning, and Erez Zadok. 2020. 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