{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T00:10:24Z","timestamp":1778890224418,"version":"3.51.4"},"reference-count":52,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Concurrency and Computation"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>In hyperscale, multi\u2010tenant serverless databases, the substantial performance disparity between cache hits (microseconds, CPU\u2010bound) and cache misses (milliseconds, I\/O\u2010bound) leads to severe interference among tenants. Traditional reactive resource management models, which respond only after an expensive cache miss occurs, fail to prevent I\/O\u2010intensive noisy neighbors from degrading the latency experienced by well\u2010behaved tenants. This paper proposes a novel preemptive isolation approach: the Predictive Cache\u2010Aware Dispatcher (PCAD). Embedded within the database proxy layer, PCAD leverages a real\u2010time machine learning model\u2014the Cache Oracle\u2014to predict the cache state of each request prior to dispatch. This foresight enables two key optimizations: (1) preemptive routing of likely cache misses to a dedicated, concurrency\u2010limited I\/O worker pool, thereby protecting the CPU\u2010optimized fast path from contention, and (2) speculative prefetching to hide disk access latency for predicted misses. Using production traces from a large\u2010scale multi\u2010tenant cloud database, we demonstrate that the Cache Oracle achieves over 91% F1\u2010score in cache miss prediction. Simulations show that PCAD effectively eliminates cross\u2010tenant interference caused by I\/O bursts, sustaining stable sub\u2010millisecond P99 latency, while speculative prefetching reduces perceived cache miss latency by over 90%. This preemptive predict and prevent approach marks a significant advancement toward more robust and high\u2010performance autonomous database systems.<\/jats:p>","DOI":"10.1002\/cpe.70470","type":"journal-article","created":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T03:13:10Z","timestamp":1764731590000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["The Cache Oracle: Preemptive Request Dispatching for I\/O\u2010Asymmetric Serverless Databases"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-8460-2074","authenticated-orcid":false,"given":"Seyed Hossein","family":"Ahmadpanah","sequence":"first","affiliation":[{"name":"Department of Computer Engineering Technical and Vocational University (TVU)  Tehran Iran"}]},{"given":"Meghdad","family":"Mirabi","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science Technical University of Darmstadt  Darmstadt Germany"}]},{"given":"Sanaz","family":"Sobhanloo","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering Technical and Vocational University (TVU)  Tehran Iran"}]},{"given":"Mobina","family":"Bayati","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering Technical and Vocational University (TVU)  Tehran Iran"}]}],"member":"311","published-online":{"date-parts":[[2025,12,2]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1561\/1900000060"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3508360"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3642977.3652096"},{"key":"e_1_2_11_5_1","article-title":"Caching Aided Multi\u2010Tenant Serverless Computing","author":"Qiao C.","year":"2024","journal-title":"ArXiv Abs\/2408.00957"},{"key":"e_1_2_11_6_1","article-title":"Curator: Efficient Indexing for Multi\u2010Tenant Vector Databases","author":"Jin Y.","year":"2024","journal-title":"ArXiv Abs\/2401.07119"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626203.3670546"},{"key":"e_1_2_11_8_1","article-title":"A Predictive Replication for Multi\u2010Tenant Databases Using Deep Learning","volume":"33","author":"Raouf A. 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