{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:28:05Z","timestamp":1750307285527,"version":"3.41.0"},"reference-count":6,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2010,11,22]],"date-time":"2010-11-22T00:00:00Z","timestamp":1290384000000},"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":["SIGMOBILE Mob. Comput. Commun. Rev."],"published-print":{"date-parts":[[2011,2,8]]},"abstract":"<jats:p>We propose a distributed scheme by which nodes select an appropriate access point to associate with using each individual device's channel utilization. Specifically, we define a new metric, channel utilization, which is defined as the ratio of required bandwidth to available bandwidth estimation. By incorporating channel utilization into the access point selection protocol, we effectively reduce unnecessary reassociations and improve upper layer performance in terms of throughput, packet delivery delay, etc. We further enhance our protocol by using reinforcement learning to adapt the scheduling of probing neighboring access points (APs), ultimately reducing probing overhead by learning from past experience whether the current operational scenario would suffer from undesirable overhead. When channel utilization is combined with adaptive probing, we observed a significant performance improvement compared to traditional association approaches.<\/jats:p>","DOI":"10.1145\/1942268.1942271","type":"journal-article","created":{"date-parts":[[2011,2,15]],"date-time":"2011-02-15T18:30:59Z","timestamp":1297794659000},"page":"4-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Improved AP association management using machine learning"],"prefix":"10.1145","volume":"14","author":[{"given":"Tingting","family":"Sun","sequence":"first","affiliation":[{"name":"WINLAB, Rutgers University, North Brunswick, NJ"}]},{"given":"Wade","family":"Trappe","sequence":"additional","affiliation":[{"name":"WINLAB, Rutgers University, North Brunswick, NJ"}]},{"given":"Yanyong","family":"Zhang","sequence":"additional","affiliation":[{"name":"WINLAB, Rutgers University, North Brunswick, NJ"}]}],"member":"320","published-online":{"date-parts":[[2010,11,22]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1080829.1080849"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/832315.837555"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1023720.1023751"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1454503.1454529"},{"key":"e_1_2_1_5_1","first-page":"1004","volume-title":"Proc. of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies","author":"Li L. E.","year":"2004","unstructured":"L. E. Li , M. Pal , and Y. R. Yang . Proportional fairness in multi-rate wireless LANs . In Proc. of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies , pages 1004 -- 1012 , April 2004 . L. E. Li, M. Pal, and Y. R. Yang. Proportional fairness in multi-rate wireless LANs. In Proc. of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies, pages 1004--1012, April 2004."},{"key":"e_1_2_1_6_1","volume-title":"Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)","author":"Sutton R. S.","year":"1998","unstructured":"R. S. Sutton and A. G. Barto . Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning) . The MIT Press , March 1998 . R. S. Sutton and A. G. Barto. Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning). The MIT Press, March 1998."}],"container-title":["ACM SIGMOBILE Mobile Computing and Communications Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1942268.1942271","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/1942268.1942271","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T10:59:36Z","timestamp":1750244376000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1942268.1942271"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,11,22]]},"references-count":6,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2011,2,8]]}},"alternative-id":["10.1145\/1942268.1942271"],"URL":"https:\/\/doi.org\/10.1145\/1942268.1942271","relation":{},"ISSN":["1559-1662","1931-1222"],"issn-type":[{"type":"print","value":"1559-1662"},{"type":"electronic","value":"1931-1222"}],"subject":[],"published":{"date-parts":[[2010,11,22]]},"assertion":[{"value":"2010-11-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}