{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:13:39Z","timestamp":1750220019461,"version":"3.41.0"},"reference-count":13,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T00:00:00Z","timestamp":1647907200000},"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":["SIGMETRICS Perform. Eval. Rev."],"published-print":{"date-parts":[[2022,3,22]]},"abstract":"<jats:p>In an EV charging facility, with multiple vehicles requesting charge simultaneously, scheduling becomes crucial to provide adequate service under vehicle sojourn time constraints. However, these departure times may not be known accurately, and typical policies such as Earliest-Deadline- First or Least-Laxity-First are affected by this uncertainty in information. In this paper, we analyze the performance of these policies under uncertain deadlines, using a meanfield approach. We characterize the deviation in individual attained service as a function of the uncertainty. Since incentives appear to under-report deadlines in order to be prioritized, we analyze a simple modification of the policies to enforce incentive compatibility. Simulation experiments are carried out with a practical data set.<\/jats:p>","DOI":"10.1145\/3529113.3529117","type":"journal-article","created":{"date-parts":[[2022,3,25]],"date-time":"2022-03-25T22:30:42Z","timestamp":1648247442000},"page":"10-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Scheduling EV charging with uncertain departure times"],"prefix":"10.1145","volume":"49","author":[{"given":"Andres","family":"Ferragut","sequence":"first","affiliation":[{"name":"Universidad ORT Uruguay, Montevideo, Uruguay"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lucas","family":"Narbondo","sequence":"additional","affiliation":[{"name":"Universidad ORT Uruguay, Montevideo, Uruguay"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fernando","family":"Paganini","sequence":"additional","affiliation":[{"name":"Universidad ORT Uruguay, Montevideo, Uruguay"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,3,25]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3152042.3152054"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCNS.2019.2915651"},{"volume-title":"A Julia language library for simulating Electrical Vehicle charging policies. https:\/\/github.com\/Grupo-MATE\/EVQueues.jl","year":"2021","key":"e_1_2_1_3_1","unstructured":"EVQueues.jl. A Julia language library for simulating Electrical Vehicle charging policies. https:\/\/github.com\/Grupo-MATE\/EVQueues.jl , 2021 . EVQueues.jl. A Julia language library for simulating Electrical Vehicle charging policies. https:\/\/github.com\/Grupo-MATE\/EVQueues.jl, 2021."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2016.2576902"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3307772.3328313"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077839.3077864"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2016.2558585"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2016.1600346CM"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/EMWRT.1990.128221"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1201\/b14876"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2016.2541305"},{"key":"e_1_2_1_12_1","volume-title":"Proc. of the 36th IFIP Performance Conference","author":"Zeballos M.","year":"2018","unstructured":"M. Zeballos , A. Ferragut , and F. Paganini . Achieving fairness for EV charging in overload: a fluid approach . In Proc. of the 36th IFIP Performance Conference , 2018 . M. Zeballos, A. Ferragut, and F. Paganini. Achieving fairness for EV charging in overload: a fluid approach. In Proc. of the 36th IFIP Performance Conference, 2018."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2019.2911231"}],"container-title":["ACM SIGMETRICS Performance Evaluation Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3529113.3529117","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3529113.3529117","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:51:25Z","timestamp":1750182685000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3529113.3529117"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,22]]},"references-count":13,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,3,22]]}},"alternative-id":["10.1145\/3529113.3529117"],"URL":"https:\/\/doi.org\/10.1145\/3529113.3529117","relation":{},"ISSN":["0163-5999"],"issn-type":[{"type":"print","value":"0163-5999"}],"subject":[],"published":{"date-parts":[[2022,3,22]]},"assertion":[{"value":"2022-03-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}