Real-Time Traffic Classification using Simple CART Forest on FPGAs

Basit Öğe Kaydı
dc.authorwosidSOYLU, Tuncay/HHN-7426-2022
dc.authorwosiderdem, oğuzhan/AAG-6229-2019
dc.contributor.authorSoylu, Tuncay
dc.contributor.authorErdem, Oguzhan
dc.contributor.authorCarus, Aydin
dc.contributor.authorGuner, Edip S.
dc.date.accessioned2024-06-12T11:19:28Z
dc.date.available2024-06-12T11:19:28Z
dc.date.issued2018
dc.departmentTrakya Üniversitesien_US
dc.descriptionIEEE 19th International Conference on High Performance Switching and Routing (HPSR) -- JUN 17-20, 2018 -- Bucharest, ROMANIAen_US
dc.description.abstractTraffic classification process categorizes internet traffic into application classes by exploiting packet header data or collected packet statistics. Real-time internet traffic classification is mostly required for network management and security applications. Machine Learning (ML) based traffic classification approaches which utilize statistical properties of traffic flows, have recently attracted great deal of attention from the researches due to its operability under encrypted traffic conditions. In this paper, we propose to use Simple Classification and Regression Trees Forest (SCF) for internet traffic classification. Our proposed scheme comprising multiple parallel trees demonstrates a substantial improvement in search delay and throughput as well as in the memory footprint when compared to a traditional single Simple CART structure. To reach high data rates for real-time classification, we also proposed a parallel and pipelined architecture on Field Programmable Gate Arrays (FPGAs) that support SCF data structure. The post place-and-route FPGA results demonstrate that our design can sustain 854 Gbps or 2669 million classification per second (MCPS) for the minimum packet size of 40 Bytes. Furthermore, our architecture shows an accuracy of 96.6719% for real internet traffic with eight application classes.en_US
dc.description.sponsorshipIEEE,IEEE Commun Socen_US
dc.identifier.isbn978-1-5386-7801-5
dc.identifier.issn2325-5595
dc.identifier.scopus2-s2.0-85073379233en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/20.500.14551/25204
dc.identifier.wosWOS:000516618000016en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2018 Ieee 19th International Conference On High Performance Switching And Routing (Ieee Hpsr)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNetworksen_US
dc.titleReal-Time Traffic Classification using Simple CART Forest on FPGAsen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu