BatteryLab: A Collaborative Platform for Power Monitoring:

Matteo Varvello*, Kleomenis Katevas, Mihai Plesa, Hamed Haddadi, Fabian Bustamante, Ben Livshits

*Corresponding author for this work

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

2 Scopus citations


Advances in cloud computing have simplified the way that both software development and testing are performed. This is not true for battery testing for which state of the art test-beds simply consist of one phone attached to a power meter. These test-beds have limited resources, access, and are overall hard to maintain; for these reasons, they often sit idle with no experiment to run. In this paper, we propose to share existing battery testbeds and transform them into vantage points of BatteryLab, a power monitoring platform offering heterogeneous devices and testing conditions. We have achieved this vision with a combination of hardware and software which allow to augment existing battery test-beds with remote capabilities. BatteryLab currently counts three vantage points, one in Europe and two in the US, hosting three Android devices and one iPhone 7. We benchmark BatteryLab with respect to the accuracy of its battery readings, system performance, and platform heterogeneity. Next, we demonstrate how measurements can be run atop of BatteryLab by developing the “Web Power Monitor” (WPM), a tool which can measure website power consumption at scale. We released WPM and used it to report on the energy consumption of Alexa’s top 1,000 websites across 3 locations and 4 devices (both Android and iOS).

Original languageEnglish (US)
Title of host publicationPassive and Active Measurement - 23rd International Conference, PAM 2022, Proceedings
EditorsOliver Hohlfeld, Giovane Moura, Cristel Pelsser
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages25
ISBN (Print)9783030987848
StatePublished - 2022
Event23rd International Conference on Passive and Active Measurement, PAM 2022 - Virtual, Online
Duration: Mar 28 2022Mar 30 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13210 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference23rd International Conference on Passive and Active Measurement, PAM 2022
CityVirtual, Online


  • Android
  • Battery
  • Performance
  • Test-bed
  • iOS

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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