{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:51:44Z","timestamp":1767340304267,"version":"3.28.0"},"reference-count":53,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,4,25]],"date-time":"2022-04-25T00:00:00Z","timestamp":1650844800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,4,25]],"date-time":"2022-04-25T00:00:00Z","timestamp":1650844800000},"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":[[2022,4,25]]},"DOI":"10.1109\/noms54207.2022.9789845","type":"proceedings-article","created":{"date-parts":[[2022,6,9]],"date-time":"2022-06-09T21:21:22Z","timestamp":1654809682000},"page":"1-9","source":"Crossref","is-referenced-by-count":6,"title":["Learning Traffic Encoding Matrices for Delay-Aware Traffic Engineering in SD-WANs"],"prefix":"10.1109","author":[{"given":"Majid","family":"Ghaderi","sequence":"first","affiliation":[{"name":"University of Calgary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjie","family":"Liu","sequence":"additional","affiliation":[{"name":"Huawei Technologies"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shihan","family":"Xiao","sequence":"additional","affiliation":[{"name":"Huawei Technologies"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fenglin","family":"Li","sequence":"additional","affiliation":[{"name":"Huawei Technologies"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"article-title":"Boosting soft actor-critic: Emphasizing recent experience without forgetting the past","year":"2019","author":"wang","key":"ref39"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/SMC.2017.8122622"},{"year":"0","key":"ref33","article-title":"One-way delay measurement techniques"},{"key":"ref32","article-title":"One-way delay measurement: State of the art","volume":"12","author":"vito","year":"2008","journal-title":"IEEE Trans Instrum Meas"},{"key":"ref31","article-title":"Multi-agent actor-critic for mixed cooperative-competitive environments","author":"lowe","year":"2017","journal-title":"Proc ACM NIPS"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/2486001.2486020"},{"key":"ref37","article-title":"Prioritized experience replay","author":"schaul","year":"2016","journal-title":"Proc ICLR"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"journal-title":"Deep Learning","year":"2016","author":"goodfellow","key":"ref35"},{"year":"0","key":"ref34","article-title":"One-way delay and jitter measurement"},{"key":"ref28","article-title":"How hard can it be? Designing and implementing a deployable multipath TCP","author":"raiciu","year":"2012","journal-title":"Proc NSENIX NDSI"},{"key":"ref27","article-title":"Continuous control with deep reinforcement learning","author":"lillicrap","year":"2016","journal-title":"Proc ICLR"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2006.875032"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2486001.2486019"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/2486001.2486012"},{"year":"0","key":"ref20","article-title":"NVIDIA BlueFiled Data Processing Unit"},{"key":"ref22","article-title":"Human-level control through deep reinforcement learning","volume":"518","author":"minh","year":"2015","journal-title":"Nature"},{"journal-title":"Reinforcement Learning An Introduction","year":"2018","author":"sutton","key":"ref21"},{"key":"ref24","article-title":"Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor","author":"haarnoja","year":"2018","journal-title":"Proc ICML"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2021.3102580"},{"article-title":"Actor-critic algorithms","year":"0","author":"levine","key":"ref26"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2916583"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/3341302.3342080"},{"key":"ref51","article-title":"A deep reinforcement learning perspective on Internet congestion control","author":"jay","year":"2019","journal-title":"Proc ICML"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2021.108033"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/3387514.3405892"},{"journal-title":"Introduction to Algorithms","year":"2009","author":"cormen","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/GLOCOM.2016.7841857"},{"year":"0","key":"ref40"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2018.00035"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/NOMS.2018.8406199"},{"key":"ref14","article-title":"Achieving high utilization with software-driven WAN","author":"dolati","year":"2019","journal-title":"Proc IEEE IWQoS"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOMW.2019.8845154"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.3000371"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-12334-4_21"},{"year":"0","key":"ref18","article-title":"What is SD-WAN?"},{"year":"0","key":"ref19","article-title":"CloudEngine 16800"},{"key":"ref4","article-title":"Semi-oblivious traffic engineering: The road not taken","author":"kumar","year":"2018","journal-title":"Proc USENIX NSDI"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2018.8485853"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2934872.2934893"},{"key":"ref5","article-title":"On optimal routing with multiple traffic matrices","author":"zhang","year":"2005","journal-title":"Proc IEEE InfoCom"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOM.2001.916625"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/1159913.1159926"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2019.2904358"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/633025.633041"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/2934872.2934890"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/2785956.2787510"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3005745.3005750"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2017.1700200"},{"journal-title":"WIDE Traffic Traces","year":"2018","key":"ref42"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2011.111002"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/2619239.2626316"},{"key":"ref43","article-title":"Deep sparse rectifier neural networks","author":"glorot","year":"2011","journal-title":"Proc AISTATS"}],"event":{"name":"NOMS 2022-2022 IEEE\/IFIP Network Operations and Management Symposium","start":{"date-parts":[[2022,4,25]]},"location":"Budapest, Hungary","end":{"date-parts":[[2022,4,29]]}},"container-title":["NOMS 2022-2022 IEEE\/IFIP Network Operations and Management Symposium"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9789703\/9789704\/09789845.pdf?arnumber=9789845","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T20:10:25Z","timestamp":1656965425000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9789845\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,25]]},"references-count":53,"URL":"https:\/\/doi.org\/10.1109\/noms54207.2022.9789845","relation":{},"subject":[],"published":{"date-parts":[[2022,4,25]]}}}