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dc.contributor.authorYazidi, Anis
dc.contributor.authorHussein, Abdi
dc.contributor.authorFeng, Boning
dc.date.accessioned2019-02-21T15:24:02Z
dc.date.accessioned2019-08-20T06:34:28Z
dc.date.available2019-02-21T15:24:02Z
dc.date.available2019-08-20T06:34:28Z
dc.date.issued2018
dc.identifier.citationYazidi A, Hussein, Feng B: Data center traffic scheduling with hot-cold link detection capabilities. In: NN N. Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems, 2018. Association for Computing Machinery (ACM) p. 268-275en
dc.identifier.isbn978-1-4503-5885-9
dc.identifier.urihttps://hdl.handle.net/10642/7437
dc.description.abstractSoftware-Defined Networking (SDN) has been one of the most discussed areas in computer networking over the last years. The field has raised an extensive amount of research, and led to a transformation of traditional network architectures. The architecture of SDN enables the separation of the control and data planes and centralizes the network intelligence. Today's data center networks are clusters of thousands of machines. The most used routing protocol in Data centers is Equal-Cost Multi-Path Protocol (ECMP) which relies on a per-flow static hashing that is known to cause bandwidth loss because of long term collisions. In this paper, a traffic engineering approach built on the concept of SDN is presented that aims to enhance the least-loaded link routing mechanism with intelligent monitoring capabilities. In this perspective, we introduce Hot and Cold link detection (HCLD) mechanism. Our HCLD permits to dynamically re-route heavy flows from heavily utilized links (Hot links) while attracting more flows to lowly utilized links (Cold links). Comprehensive experimental results show that the devised flow scheduling solution outperforms the widely used ECMP. Results also demonstrate that dynamic monitoring of traffic statistics could be used to better utilize the total available bandwidth of the network in a reactive manner.en
dc.language.isoenen
dc.publisherACMen
dc.relation.ispartofseriesRACS '18 Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems;
dc.rightsDen aksepterte fagfellevurderte postprint-versjonen av kapittelet er tillatt å arkivere i institusjonelle arkiv. Kapittelets forlegger har lagt ved følgende erklæring om bruk: Permission to make digital or hard copies of all or part of this work for personal or class room use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.en
dc.subjectData centersen
dc.subjectTraffic engineeringen
dc.subjectSDNen
dc.subjectHot linksen
dc.subjectCold linksen
dc.subjectEqual-cost multi-path protocols
dc.titleData center traffic scheduling with hot-cold link detection capabilitiesen
dc.typeChapter
dc.typeChapteren
dc.typePeer revieweden
dc.date.updated2019-02-21T15:24:02Z
dc.description.versionacceptedVersionen
dc.identifier.doihttps://dx.doi.org/10.1145/3264746.3264797
dc.identifier.cristin1679700
dc.source.isbn978-1-4503-5885-9


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