{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T14:21:01Z","timestamp":1761402061010,"version":"3.44.0"},"reference-count":33,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,10]]},"DOI":"10.1109\/lcn44214.2019.8990758","type":"proceedings-article","created":{"date-parts":[[2020,2,14]],"date-time":"2020-02-14T04:17:26Z","timestamp":1581653846000},"page":"340-347","source":"Crossref","is-referenced-by-count":7,"title":["RL-Sketch: Scaling Reinforcement Learning for Adaptive and Automate Anomaly Detection in Network Data Streams"],"prefix":"10.1109","author":[{"given":"Zhengyan","family":"Zhou","sequence":"first","affiliation":[{"name":"Fuzhou University,College of Mathematics and Computer Science"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fuzhou University,College of Mathematics and Computer Science"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"Hong","sequence":"additional","affiliation":[{"name":"University of Alabama,Department of Computer Science"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3229543.3229545"},{"key":"ref32","article-title":"Flowradar: A better netflow for data centers","author":"li","year":"0","journal-title":"Proceedings of NSDI’14"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2934872.2934906"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOM.2012.6195691"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2005.860096"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3050220.3063772"},{"key":"ref12","first-page":"909","article-title":"Heavykeeper: An accurate algorithm for finding top-k elephant flows","author":"gong","year":"2018","journal-title":"Proceedings of ATC’14"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2017.8057216"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2017.8057215"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2014.6848076"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.1998.712192"},{"key":"ref17","first-page":"529","article-title":"Human-level control through deep reinforcement learning","author":"mnih","year":"2015"},{"journal-title":"The CAIDA Anonymized Internet Traces 2016 Dataset","year":"2018","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/BF00992698"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2007.896150"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3098822.3098831"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/948205.948236"},{"key":"ref3","first-page":"29","article-title":"Software defined traffic measurement with opensketch","author":"yu","year":"2013","journal-title":"Proceedings of NSDI’14"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3230543.3230544"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2010.06.018"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3230543.3230559"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737499"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2015.08.025"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3098822.3098832"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-24698-5_7"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-009-0172-z"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/0893-6080(91)90009-T"},{"key":"ref22","doi-asserted-by":"crossref","DOI":"10.1002\/9780470316887","author":"puterman","year":"1994","journal-title":"Markov Decision Processes Discrete Stochastic Dynamic Programming"},{"key":"ref21","first-page":"2015","article-title":"Deep Reinforcement Learning with Double Q-learning","author":"van hasselt","year":"0","journal-title":"ArXiv e-prints"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/9.580874"},{"key":"ref23","article-title":"Reinforcement learning for robots using neural networks","author":"lin","year":"1993","journal-title":"Technical Report"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45465-9_59"},{"journal-title":"Documentation Tensorforce","year":"2019","key":"ref25"}],"event":{"name":"2019 IEEE 44th Conference on Local Computer Networks (LCN)","start":{"date-parts":[[2019,10,14]]},"location":"Osnabrueck, Germany","end":{"date-parts":[[2019,10,17]]}},"container-title":["2019 IEEE 44th Conference on Local Computer Networks (LCN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8970147\/8990670\/08990758.pdf?arnumber=8990758","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T18:37:18Z","timestamp":1755715038000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8990758\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/lcn44214.2019.8990758","relation":{},"subject":[],"published":{"date-parts":[[2019,10]]}}}