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Latency Imbalance Among Internet Load-Balanced Paths: A Cloud-Centric View

Published: 09 July 2020 Publication History

Abstract

Load balancers choose among load-balanced paths to distribute traffic as if it makes no difference using one path or another. This work shows that the latency difference between load-balanced paths (called latency imbalance), previously deemed insignificant, is now prevalent from the perspective of the cloud and affects various latency-sensitive applications. In this work, we present the first large-scale measurement study of latency imbalance from a cloudcentric view. Using public cloud around the globe, we measure latency imbalance both between data centers (DCs) in the cloud and from the cloud to the public Internet. Our key findings include that 1) Amazon's and Alibaba's clouds together have latency difference between load-balanced paths larger than 20ms to 21% of public IPv4 addresses; 2) Google's secret in having lower latency imbalance than other clouds is to use its own well-balanced private WANs to transit traffic close to the destinations and that 3) latency imbalance is also prevalent between DCs in the cloud, where 8 pairs of DCs are found to have load-balanced paths with latency difference larger than 40ms. We further evaluate the impact of latency imbalance on three applications (i.e., NTP, delay-based geolocation and VoIP) and propose potential solutions to improve application performance. Our experiments show that all three applications can benefit from considering latency imbalance, where the accuracy of delay-based geolocation can be greatly improved by simply changing how ping measures the minimum path latency.

References

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Brice Augustin, Timur Friedman, and Renata Teixeira. Measuring load-balanced paths in the Internet. In IMC, 2007.
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Brice Augustin, Xavier Cuvellier, Benjamin Orgogozo, Fabien Viger, Timur Friedman, Matthieu Latapy, Clémence Magnien, and Renata Teixeira. Avoiding traceroute anomalies with Paris Traceroute. In IMC, 2006.
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Zachary Weinberg, Shinyoung Cho, Nicolas Christin, Vyas Sekar, and Phillipa Gill. How to catch when proxies lie: Verifying the physical locations of network proxies with active geolocation. In IMC, pages 203--217, 2018.
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Sathiya Kumaran Mani, Ramakrishnan Durairajan, Paul Barford, and Joel Sommers. MNTP: Enhancing time synchronization for mobile devices. In IMC, 2016.
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Cristel Pelsser, Luca Cittadini, Stefano Vissicchio, and Randy Bush. From Paris to Tokyo: On the suitability of ping to measure latency. In IMC, 2013.
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Kevin Vermeulen, Stephen D. Strowes, Olivier Fourmaux, and Timur Friedman. Multilevel MDA-Lite Paris Traceroute. In IMC, 2018.
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Mark Gondree and Zachary NJ Peterson. Geolocation of data in the cloud. In Proceedings of the third ACM conference on Data and application security and privacy, pages 25--36, 2013.
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Junchen Jiang et al. Via: Improving Internet telephony call quality using predictive relay selection. In SIGCOMM, 2016.
[9]
Our tool and dataset. https://github.com/yibopi/latency-imbalance.
[10]
Yibo Pi, Sugih Jamin, Peter Danzig, and Feng Qian. Latency imbalance among Internet load-balanced paths: A cloud-centric view. In SIGMETRICS, 2020.
  1. Latency Imbalance Among Internet Load-Balanced Paths: A Cloud-Centric View

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    Published In

    cover image ACM SIGMETRICS Performance Evaluation Review
    ACM SIGMETRICS Performance Evaluation Review  Volume 48, Issue 1
    June 2020
    110 pages
    ISSN:0163-5999
    DOI:10.1145/3410048
    Issue’s Table of Contents
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 09 July 2020
    Published in SIGMETRICS Volume 48, Issue 1

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    Author Tags

    1. cloud
    2. latency imbalance
    3. latency-sensitive
    4. load-balanced paths

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