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MP-HULA: Multipath transport aware load balancing using programmable data planes
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-7734-1653
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-9446-8143
Brown University, United States.
Networking Research - Ericsson, United States.
2018 (English)In: NetCompute 2018 - Proceedings of the 2018 Morning Workshop on In-Network Computing, Part of SIGCOMM 2018, Association for Computing Machinery, Inc , 2018, p. 7-13Conference paper, Published paper (Refereed)
Abstract [en]

Datacenter networks ofer a large degree of multipath in order to provide large bisectional bandwidth. The end-to-end performance is determined by the load-balancing strategy which needs to be designed to efectively manage congestion. Consequently, congestion aware load-balancing strategies such as CONGA or HULA have been designed. Recently, more and more applications that are hosted on cloud servers use multipath transport protocols such as MPTCP. However, in the presence of MPTCP, existing load-balancing schemes including ECMP, HULA or CONGA may lead to suboptimal forwarding decisions where multiple MPTCP subfows of one connection are pinned on the same bottleneck link. In this paper, we present MP-HULA, a transport layer multi-path aware load-balancing scheme using Programmable Data Planes. First, instead of tracking congestion information for the best path towards the destination, each MP-HULA switch tracks congestion information for the best-k paths to a destination through the neighbor switches. Second, we design MP-HULA using Programmable Data Planes, where each leaf switch can identify, using P4, which MPTCP subfow belongs to which connection. MP-HULA then load-balances diferent MPTCP subfows of a MPTCP connection on diferent next hops considering congestion state while aggregating bandwidth. Our evaluation shows that MP-HULA with MPTCP outperforms HULA in average flow completion time (2.1x at 50% load, 1.7x at 80% load).

Place, publisher, year, edition, pages
Association for Computing Machinery, Inc , 2018. p. 7-13
Keywords [en]
In-network load balancing, Multipath, Network congestion, Programmable switches, Bandwidth, End-to-end performance, In networks, Load balancing strategy, Load-balancing schemes, Multipath transport protocols, Network congestions, Traffic congestion
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-70360DOI: 10.1145/3229591.3229596Scopus ID: 2-s2.0-85056382917ISBN: 9781450359085 (print)ISBN: 978-1-4503-5908-5 (print)OAI: oai:DiVA.org:kau-70360DiVA, id: diva2:1266876
Conference
ACM SIGCOMM Workshop on In-Network Computing, NetCompute 2018, 20 August 2018
Projects
HITS, 4707
Funder
Knowledge FoundationAvailable from: 2018-11-29 Created: 2018-11-29 Last updated: 2019-04-24Bibliographically approved

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Hernandez Benet, CristianKassler, Andreas

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