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Stateless CPU-aware datacenter load-balancing
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS, Network Systems Laboratory (NS Lab).ORCID iD: 0000-0003-1269-2190
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS, Network Systems Laboratory (NS Lab).ORCID iD: 0000-0002-9675-9729
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS.ORCID iD: 0000-0002-6066-746X
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS.ORCID iD: 0000-0002-1256-1070
2020 (English)In: Poster: Stateless CPU-aware datacenter load-balancing, Association for Computing Machinery (ACM) , 2020, p. 548-549Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Today, datacenter operators deploy Load-balancers (LBs) to efficiently utilize server resources, but must over-provision server resources (by up to 30%) because of load imbalances and the desire to bound tail service latency. We posit one of the reasons for these imbalances is the lack of per-core load statistics in existing LBs. As a first step, we designed CrossRSS, a CPU core-aware LB that dynamically assigns incoming connections to the least loaded cores in the server pool. CrossRSS leverages knowledge of the dispatching by each server's Network Interface Card (NIC) to specific cores to reduce imbalances by more than an order of magnitude compared to existing LBs in a proof-of-concept datacenter environment, processing 12% more packets with the same number of cores.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2020. p. 548-549
Series
CoNEXT '20
Keywords [en]
networking, load-balancing, packet scheduling, high-speed networking, intra-server load-balancing, receive side scaling, network function virtualization, RSS++
National Category
Computer Systems Communication Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-286811DOI: 10.1145/3386367.3431672Scopus ID: 2-s2.0-85097602615OAI: oai:DiVA.org:kth-286811DiVA, id: diva2:1505249
Conference
International Conference on emerging Networking EXperiments and Technologies
Funder
EU, European Research Council, ULTRASwedish Foundation for Strategic Research , TCC
Note

QC 20210824

Available from: 2020-11-30 Created: 2020-11-30 Last updated: 2022-06-25Bibliographically approved

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fulltext(1525 kB)489 downloads
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Barbette, TomChiesa, MarcoMaguire Jr., Gerald Q.Kostic, Dejan

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CiteExportLink to record
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Citation style
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