research-article

Combining RTT and ECN for RoCEv2 Protocol

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Min XieAuthors Info & Claims

HPCCT & BDAI '20: Proceedings of the 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data and Artificial Intelligence

Pages 158 - 164

https://doi.org/10.1145/3409501.3409509

Published: 25 August 2020 Publication History

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Abstract

Remote direct memory access (RDMA) has the advantages of direct user-level access to HW, asynchronous communication, etc. RoCEv2 protocol enables RDMA technology to be used in large-scale data centers over Ethernet. It provides high throughput and low latency for data center, but it faces the problem of network congestion caused by RoCEv2 data flow. Efficient congestion control strategy plays an important role in the performance of RoCEv2 based data center network. At present, the network congestion control algorithms for RoCEv2 protocol are mainly based on ECN marked DCQCN and RTT based TIMELY. ECN and RTT have different characteristics and advantages. ECN is more effective to prevent packet losses; whereas RTT controls end-to-end queuing delay better. In this paper, a new algorithm RTT_DCQCN is presented for congestion control which is based on DCQCN. In RTT_DCQCN, the CNP generation mechanism and rate adjustment strategy are optimized; and the scheme of introducing RTT signal into DCQCN is proposed, in which the congestion degree is judged by using ECN and RTT together. The RoCEv2 protocol is implemented on ns-3 network simulation platform. The simulation experiment on ns-3 proved that RTT_DCQCN is valid for the aim of improving stability, fairness and throughput of the RoCEv2 data flows.

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Cited By

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Zheng HHuang CHan XZheng JWang XTian CDou WChen GSekar VYu MSeneviratne AVeitch D(2024)μMon: Empowering Microsecond-level Network Monitoring with WaveletsProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672236(274-290)Online publication date: 4-Aug-2024
https://dl.acm.org/doi/10.1145/3651890.3672236
Wang TKan HSun QXiao SWang S(2022)Congestion Detection and Link Control via Feedback in RDMA Transmission2022 International Conference on Service Science (ICSS)10.1109/ICSS55994.2022.00010(1-4)Online publication date: May-2022
https://doi.org/10.1109/ICSS55994.2022.00010
Shpigelman YShainer GGraham RQin YCisneros-Stoianowski GStunkel C(2022)NVIDIA’s Quantum InfiniBand Network Congestion Control Technology and Its Impact on Application PerformanceHigh Performance Computing10.1007/978-3-031-07312-0_2(26-43)Online publication date: 29-May-2022
https://doi.org/10.1007/978-3-031-07312-0_2

Index Terms

Combining RTT and ECN for RoCEv2 Protocol
1. Networks
  1. Network types
    1. Data center networks

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Published In

HPCCT & BDAI '20: Proceedings of the 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data and Artificial Intelligence

July 2020

276 pages

ISBN:9781450375603

DOI:10.1145/3409501

Permission to make digital or hard copies of all or part of this work for personal or classroom 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. Request permissions from [email protected]

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Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 August 2020

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HPCCT & BDAI 2020

HPCCT & BDAI 2020: 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data and Artificial Intelligence

July 3 - 6, 2020

Qingdao, China

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Cited By

View all

Zheng HHuang CHan XZheng JWang XTian CDou WChen GSekar VYu MSeneviratne AVeitch D(2024)μMon: Empowering Microsecond-level Network Monitoring with WaveletsProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672236(274-290)Online publication date: 4-Aug-2024
https://dl.acm.org/doi/10.1145/3651890.3672236
Wang TKan HSun QXiao SWang S(2022)Congestion Detection and Link Control via Feedback in RDMA Transmission2022 International Conference on Service Science (ICSS)10.1109/ICSS55994.2022.00010(1-4)Online publication date: May-2022
https://doi.org/10.1109/ICSS55994.2022.00010
Shpigelman YShainer GGraham RQin YCisneros-Stoianowski GStunkel C(2022)NVIDIA’s Quantum InfiniBand Network Congestion Control Technology and Its Impact on Application PerformanceHigh Performance Computing10.1007/978-3-031-07312-0_2(26-43)Online publication date: 29-May-2022
https://doi.org/10.1007/978-3-031-07312-0_2

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