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dDrops: Detecting silent packet drops on programmable data plane

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posted on 2022-08-09, 11:08 authored by Mimi Qian, Lin Cui, Xiaoquan Zhang, Fung Po TsoFung Po Tso, Yuhui Deng
Silent packet drops are common in data center networks, and are a major cause of network performance anomalies (NPAs) that have significant impacts on application performance and network management. However, existing solutions using coarse-grained statistics and flow-level telemetry either fail to provide precise location of packet drops or incur large overhead. This paper presents dDrops, a packet-level telemetry based on programmable data plane to detect and retrieve details of silent packet drops immediately when they happen. dDrops can dynamically adapt to varying ratios of silent packet drops for different ports on a switch to improve performance of silent packet drops detection. Moreover, a dynamic memory management scheme is also designed to efficiently use the limited memory on the data plane of switch. dDrops has been implemented on both P4 hardware programmable switches (based on Intel Tofino ASIC) and BMv2. Extensive experiment results show that dDrops is able to detect and locate the silent packet drops within 5 ms (including detailed information of dropped packets), and reduce the memory consumption by up to 50%.

Funding

National Natural Science Foundation of China (NSFC) No. 62172189

National Natural Science Foundation of China (NSFC) No.61772235

Natural Science Foundation of Guangdong Province, China No. 2020A1515010771

Natural Science Foundation of Guangdong Province, China No. 2021B1515120048

Science and Technology Program of Guangzhou No. 202002030372

SYNC: Synergistic Network Policy Management for Cloud Data Centres

Engineering and Physical Sciences Research Council

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FRuIT: The Federated RaspberryPi Micro-Infrastructure Testbed

Engineering and Physical Sciences Research Council

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InnovateUK grant 106199-47198

History

School

  • Science

Department

  • Computer Science

Published in

Computer Networks

Volume

214

Issue

2022

Publisher

Elsevier

Version

  • AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Computer Networks and the definitive published version is available at https://doi.org/10.1016/j.comnet.2022.109171

Acceptance date

2022-07-08

Publication date

2022-07-14

Copyright date

2022

ISSN

1389-1286

Language

  • en

Depositor

Dr Posco Tso. Deposit date: 8 August 2022

Article number

109171

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