Ebserver: Automating Resource-Usage Data Collection of Android Applications

Wellington Oliveira*, Bernardo Moraes, Fernando Castor, Joao Paulo Fernandes

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Mobile applications are a typical component of people's routines. Because of that, there is fierce competition for mobile users' attention, creating pressure for mobile developers to optimize their applications in a number of ways, such as making them faster, reducing their energy consumption, or their memory usage. To understand their application resource usage, developers need to execute their app, collect data from that execution and analyze how it behaves. Researchers must also go through this process when evaluating optimizations and techniques to reduce resource usage. This error-prone experimentation process can take hours of repetitive work if done manually. In this paper, we present EBSERVER, a general-purpose measurement automation tool to collect Android device data during application executions. EBSERVER is simple to configure and extend, requiring very little instrumentation code to use. It enables users to collect execution metrics on a per-process basis from an application execution automatically. Examples of such metrics include energy consumption, CPU usage, execution time, and memory usage. EBSERVER makes it possible for applications to run multiple times in an automated manner, eliminates the need to predict the time that applications or benchmarks will run in an experiment, and is compatible with contemporary Android UI testing tools. EBSERVER has been employed in multiple experiments, including experiments that do not have involvement of its authors.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE/ACM 10th International Conference on Mobile Software Engineering and Systems, MOBILESoft 2023
PublisherIEEE
Pages55-59
Number of pages5
ISBN (Electronic)9798350311822
ISBN (Print)9798350311822
DOIs
Publication statusPublished - 11 Jul 2023
Event10th IEEE/ACM International Conference on Mobile Software Engineering and Systems, MOBILESoft 2023 - Melbourne, Australia
Duration: 14 May 202315 May 2023

Publication series

NameProceedings - 2023 IEEE/ACM 10th International Conference on Mobile Software Engineering and Systems, MOBILESoft 2023

Conference

Conference10th IEEE/ACM International Conference on Mobile Software Engineering and Systems, MOBILESoft 2023
Country/TerritoryAustralia
CityMelbourne
Period14/05/2315/05/23

Bibliographical note

Funding Information:
This research was partially by FEDER from the European Union through CENTRO 2020 under project CENTRO-01-0247-FEDER-047256 – GreenStamp: Mobile Energy Efficiency Services, and Base Funding - UIDB/00027/2020 of the Artificial Intelligence and Computer Science Laboratory – LIACC - by national funds through the FCT/MCTES (PIDDAC), and by FCT in the LASIGE Research Unit under the ref. UIDB/00408/2020 and UIDP/00408/2020 and the RAP project under the reference EXPL/CCI-COM/1306/2021, and INES 2.0, (FACEPE PRONEX APQ 0388-1.03/14 and APQ-0399-1.03/17, CNPq 465614/2014-0).

Funding Information:
This research was partially by FEDER from the European Union through CENTRO 2020 under project CENTRO-01-0247-FEDER- 047256 - GreenStamp: Mobile Energy Efficiency Services, and Base Funding - UIDB/00027/2020 of the Artificial Intelligence and Computer Science Laboratory - LIACC - by national funds through the FCT/MCTES (PIDDAC), and by FCT in the LASIGE Research Unit under the ref. UIDB/00408/2020 and UIDP/00408/2020 and the RAP project under the reference EXPL/CCI- COM/1306/2021, and INES 2.0, (FACEPE PRONEX APQ 0388-1.03/14 and APQ-0399-1.03/17, CNPq 465614/2014-0).

Publisher Copyright:
© 2023 IEEE.

Funding

This research was partially by FEDER from the European Union through CENTRO 2020 under project CENTRO-01-0247-FEDER-047256 – GreenStamp: Mobile Energy Efficiency Services, and Base Funding - UIDB/00027/2020 of the Artificial Intelligence and Computer Science Laboratory – LIACC - by national funds through the FCT/MCTES (PIDDAC), and by FCT in the LASIGE Research Unit under the ref. UIDB/00408/2020 and UIDP/00408/2020 and the RAP project under the reference EXPL/CCI-COM/1306/2021, and INES 2.0, (FACEPE PRONEX APQ 0388-1.03/14 and APQ-0399-1.03/17, CNPq 465614/2014-0). This research was partially by FEDER from the European Union through CENTRO 2020 under project CENTRO-01-0247-FEDER- 047256 - GreenStamp: Mobile Energy Efficiency Services, and Base Funding - UIDB/00027/2020 of the Artificial Intelligence and Computer Science Laboratory - LIACC - by national funds through the FCT/MCTES (PIDDAC), and by FCT in the LASIGE Research Unit under the ref. UIDB/00408/2020 and UIDP/00408/2020 and the RAP project under the reference EXPL/CCI- COM/1306/2021, and INES 2.0, (FACEPE PRONEX APQ 0388-1.03/14 and APQ-0399-1.03/17, CNPq 465614/2014-0).

Keywords

  • Android
  • Energy
  • Metrics
  • Performance
  • Tool

Fingerprint

Dive into the research topics of 'Ebserver: Automating Resource-Usage Data Collection of Android Applications'. Together they form a unique fingerprint.

Cite this