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RSS++: load and state-aware receive side scaling
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: 0000-0002-3890-6583
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS, Radio Systems Laboratory (RS Lab).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
2019 (English)In: Proceedings of the 15th International Conference on emerging Networking EXperiments and Technologies / [ed] ACM, Orlando, FL, USA: Association for Computing Machinery (ACM), 2019Conference paper, Published paper (Refereed)
Abstract [en]

While the current literature typically focuses on load-balancing among multiple servers, in this paper, we demonstrate the importance of load-balancing within a single machine (potentially with hundreds of CPU cores). In this context, we propose a new load-balancing technique (RSS++) that dynamically modifies the receive side scaling (RSS) indirection table to spread the load across the CPU cores in a more optimal way. RSS++ incurs up to 14x lower 95th percentile tail latency and orders of magnitude fewer packet drops compared to RSS under high CPU utilization. RSS++ allows higher CPU utilization and dynamic scaling of the number of allocated CPU cores to accommodate the input load, while avoiding the typical 25% over-provisioning. RSS++ has been implemented for both (i) DPDK and (ii) the Linux kernel. Additionally, we implement a new state migration technique, which facilitates sharding and reduces contention between CPU cores accessing per-flow data. RSS++ keeps the flow-state by groups that can be migrated at once, leading to a 20% higher efficiency than a state of the art shared flow table.

Place, publisher, year, edition, pages
Orlando, FL, USA: Association for Computing Machinery (ACM), 2019.
Keywords [en]
networking, load-balancing, packet scheduling, high-speed networking, intra-server load-balancing, receive side scaling, network function virtualization, RSS++
National Category
Communication Systems Computer Systems Computer Sciences
Research subject
Information and Communication Technology; Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-263941DOI: 10.1145/3359989.3365412ISBN: 978-1-4503-6998-5 (electronic)OAI: oai:DiVA.org:kth-263941DiVA, id: diva2:1371780
Conference
CoNEXT' 19
Funder
Swedish Foundation for Strategic Research , TCCEU, European Research Council, 770889
Note

QC 20191126

Available from: 2019-11-20 Created: 2019-11-20 Last updated: 2019-11-26Bibliographically approved

Open Access in DiVA

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Publisher's full texthttps://conferences2.sigcomm.org/co-next/2019/#!/home

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