{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T15:03:04Z","timestamp":1776351784109,"version":"3.51.2"},"reference-count":37,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2019,5,21]],"date-time":"2019-05-21T00:00:00Z","timestamp":1558396800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010418","name":"Institute for Information and communications Technology Promotion","doi-asserted-by":"publisher","award":["2016-0-00133"],"award-info":[{"award-number":["2016-0-00133"]}],"id":[{"id":"10.13039\/501100010418","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010418","name":"Institute for Information and communications Technology Promotion","doi-asserted-by":"publisher","award":["2015-0-00914"],"award-info":[{"award-number":["2015-0-00914"]}],"id":[{"id":"10.13039\/501100010418","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2016R1A6A3A11931385"],"award-info":[{"award-number":["2016R1A6A3A11931385"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2017R1A2B2009095"],"award-info":[{"award-number":["2017R1A2B2009095"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The usage of multiple flow tables (MFT) has significantly extended the flexibility and applicability of software-defined networking (SDN). However, the size of MFT is usually limited due to the use of expensive ternary content addressable memory (TCAM). Moreover, the pipeline mechanism of MFT causes long flow processing time. In this paper a novel approach called Agg-ExTable is proposed to efficiently manage the MFT. Here the flow entries in MFT are periodically aggregated by applying pruning and the Quine\u2013Mccluskey algorithm. Utilizing the memory space saved by the aggregation, a front-end ExTable is constructed, keeping popular flow entries for early match. Popular entries are decided by the Hidden Markov model based on the match frequency and match probability. Computer simulation reveals that the proposed scheme is able to save about 45% of space of MFT, and efficiently decrease the flow processing time compared to the existing schemes.<\/jats:p>","DOI":"10.3390\/s19102341","type":"journal-article","created":{"date-parts":[[2019,5,21]],"date-time":"2019-05-21T10:52:51Z","timestamp":1558435971000},"page":"2341","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Entry Aggregation and Early Match Using Hidden Markov Model of Flow Table in SDN"],"prefix":"10.3390","volume":"19","author":[{"given":"Cheng","family":"Wang","sequence":"first","affiliation":[{"name":"Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hee Yong","family":"Youn","sequence":"additional","affiliation":[{"name":"College of Software, Sungkyunkwan University, Suwon 16419, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1145\/1355734.1355746","article-title":"OpenFlow: Enabling innovation in campus networks","volume":"38","author":"McKeown","year":"2008","journal-title":"ACM SIGCOMM Comput. 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