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

Yibo Pi, Sugih Jamin, Peter Danzig, Feng Qian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

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 cloud-centric 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.

Original languageEnglish (US)
Title of host publicationSIGMETRICS Performance 2020 - Abstracts of the 2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems
PublisherAssociation for Computing Machinery, Inc
Pages65-66
Number of pages2
ISBN (Electronic)9781450379854
DOIs
StatePublished - Jun 8 2020
Event2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2020 - Boston, United States
Duration: Jun 8 2020Jun 12 2020

Publication series

NameSIGMETRICS Performance 2020 - Abstracts of the 2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems

Conference

Conference2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2020
CountryUnited States
CityBoston
Period6/8/206/12/20

Bibliographical note

Publisher Copyright:
© 2019 Owner/Author.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • cloud
  • latency imbalance
  • latency-sensitive
  • load-balanced paths

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