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Generic and automatic address configuration for data center networks

Published: 30 August 2010 Publication History

Abstract

Data center networks encode locality and topology information into their server and switch addresses for performance and routing purposes. For this reason, the traditional address configuration protocols such as DHCP require huge amount of manual input, leaving them error-prone.
In this paper, we present DAC, a generic and automatic Data center Address Configuration system. With an automatically generated blueprint which defines the connections of servers and switches labeled by logical IDs, e.g., IP addresses, DAC first learns the physical topology labeled by device IDs, e.g., MAC addresses. Then at the core of DAC is its device-to-logical ID mapping and malfunction detection. DAC makes an innovation in abstracting the device-to-logical ID mapping to the graph isomorphism problem, and solves it with low time-complexity by leveraging the attributes of data center network topologies. Its malfunction detection scheme detects errors such as device and link failures and miswirings, including the most difficult case where miswirings do not cause any node degree change.
We have evaluated DAC via simulation, implementation and experiments. Our simulation results show that DAC can accurately find all the hardest-to-detect malfunctions and can autoconfigure a large data center with 3.8 million devices in 46 seconds. In our implementation, we successfully autoconfigure a small 64-server BCube network within 300 milliseconds and show that DAC is a viable solution for data center autoconfiguration.

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      cover image ACM Conferences
      SIGCOMM '10: Proceedings of the ACM SIGCOMM 2010 conference
      August 2010
      500 pages
      ISBN:9781450302012
      DOI:10.1145/1851182
      • cover image ACM SIGCOMM Computer Communication Review
        ACM SIGCOMM Computer Communication Review  Volume 40, Issue 4
        SIGCOMM '10
        October 2010
        481 pages
        ISSN:0146-4833
        DOI:10.1145/1851275
        Issue’s Table of Contents
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      Published: 30 August 2010

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      Author Tags

      1. address configuration
      2. data center networks
      3. graph isomorphism

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      SIGCOMM '10: ACM SIGCOMM 2010 Conference
      August 30 - September 3, 2010
      New Delhi, India

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      • (2020)Large scale symmetric network malfunction detectionProceedings of the SIGCOMM '20 Poster and Demo Sessions10.1145/3405837.3411373(12-14)Online publication date: 10-Aug-2020
      • (2019)A3Proceedings of the ACM SIGCOMM 2019 Conference Posters and Demos10.1145/3342280.3342295(24-26)Online publication date: 19-Aug-2019
      • (2019)Graph Filter: Enabling Efficient Topology CalibrationIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2019.292500130:12(2730-2742)Online publication date: 1-Dec-2019
      • (2019)Semantic-Aware Data Cube for Cloud NetworksSearchable Storage in Cloud Computing10.1007/978-981-13-2721-6_8(179-204)Online publication date: 9-Feb-2019
      • (2017)Toward A Scalable, Fault-Tolerant, High-Performance Optical Data Center ArchitectureIEEE/ACM Transactions on Networking10.1109/TNET.2017.268837625:4(2281-2294)Online publication date: 1-Aug-2017
      • (2017)Topology calibration in data centers2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)10.1109/IWQoS.2017.7969137(1-5)Online publication date: Jun-2017
      • (2017)OSA: An Optical Switching Architecture for Data Center Networks with Unprecedented FlexibilityOptical Switching in Next Generation Data Centers10.1007/978-3-319-61052-8_4(73-91)Online publication date: 30-Aug-2017
      • (2016)Explicit Path Control in Commodity Data CentersIEEE/ACM Transactions on Networking10.1109/TNET.2015.248298824:5(2768-2781)Online publication date: 1-Oct-2016
      • (2016)Scalable Monitoring and Optimization Techniques for Megascale Data CentersJournal of Lightwave Technology10.1109/JLT.2016.252265434:8(1980-1989)Online publication date: 15-Apr-2016
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