article

Monitoring energy hotspots in software

Authors:

Adel Noureddine,

Lionel SeinturierAuthors Info & Claims

Automated Software Engineering, Volume 22, Issue 3

Pages 291 - 332

https://doi.org/10.1007/s10515-014-0171-1

Published: 01 September 2015 Publication History

Abstract

Green IT has emerged as a discipline concerned with the optimization of software solutions with regards to their energy consumption. In this domain, most of the state-of-the-art solutions concentrate on coarse-grained approaches to monitor the energy consumption of a device or a process. In this paper, we report on a fine-grained runtime energy monitoring framework we developed to help developers to diagnose energy hotspots with a better accuracy. Concretely, our approach adopts a two-layer architecture including OS-level and process-level energy monitoring. OS-level energy monitoring estimates the energy consumption of processes according to different hardware devices (CPU, network card). Process-level energy monitoring focuses on Java-based applications and builds on OS-level energy monitoring to provide an estimation of energy consumption at the granularity of classes and methods. We argue that this per-method analysis of energy consumption provides better insights to the application in order to identify potential energy hotspots. In particular, our preliminary validation demonstrates that we can monitor energy hotspots of Jetty web servers and monitor their variations under stress scenarios.

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Cited By

Siavvas MTsoukalas DMarantos CPapadopoulos LLamprakos CMatei OStrydis CSiddiqi MChrobocinski PFilus KDomańska JAvgeriou PAmpatzoglou ASoudris DChatzigeorgiou AGelenbe EKehagias DTzovaras D(2024)SDK4ED: a platform for building energy efficient, dependable, and maintainable embedded softwareAutomated Software Engineering10.1007/s10515-024-00450-z31:2Online publication date: 11-Jun-2024
https://dl.acm.org/doi/10.1007/s10515-024-00450-z
Alvarez-Valera HMaurice ARavat FSong JRoose PValles-Parlangeau N(2024)Energy Measurement System for Data Lake: An Initial ApproachIntelligent Information and Database Systems10.1007/978-981-97-4982-9_2(15-27)Online publication date: 15-Apr-2024
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Liu KMahmoud KYoo JLiu Y(2023)VincentScience of Computer Programming10.1016/j.scico.2023.102962230:COnline publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1016/j.scico.2023.102962
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Monitoring energy hotspots in software

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Published In

cover image Automated Software Engineering

Automated Software Engineering Volume 22, Issue 3

September 2015

147 pages

ISSN:0928-8910

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Copyright © Copyright © 2015 Springer Science+Business Media New York.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 September 2015

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Cited By

Siavvas MTsoukalas DMarantos CPapadopoulos LLamprakos CMatei OStrydis CSiddiqi MChrobocinski PFilus KDomańska JAvgeriou PAmpatzoglou ASoudris DChatzigeorgiou AGelenbe EKehagias DTzovaras D(2024)SDK4ED: a platform for building energy efficient, dependable, and maintainable embedded softwareAutomated Software Engineering10.1007/s10515-024-00450-z31:2Online publication date: 11-Jun-2024
https://dl.acm.org/doi/10.1007/s10515-024-00450-z
Alvarez-Valera HMaurice ARavat FSong JRoose PValles-Parlangeau N(2024)Energy Measurement System for Data Lake: An Initial ApproachIntelligent Information and Database Systems10.1007/978-981-97-4982-9_2(15-27)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1007/978-981-97-4982-9_2
Liu KMahmoud KYoo JLiu Y(2023)VincentScience of Computer Programming10.1016/j.scico.2023.102962230:COnline publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1016/j.scico.2023.102962
Athanasopoulos DMcEwen M(2023)Multi-objective empirical computational complexity of single-tenant service instances deployed at the EdgeJournal of Systems and Software10.1016/j.jss.2023.111665200:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.jss.2023.111665
Liu CChakraborty AChawla NRoggel NYin HStavrou ACremers CShi E(2022)Frequency Throttling Side-Channel AttackProceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security10.1145/3548606.3560682(1977-1991)Online publication date: 7-Nov-2022
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Sun YFang JChen YLiu YChen ZGuo SChen XTan Z(2022)Energy inefficiency diagnosis for Android applications: a literature reviewFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-021-0532-417:1Online publication date: 8-Aug-2022
https://dl.acm.org/doi/10.1007/s11704-021-0532-4
Guégain ÉQuinton CRouvoy RMousavi MSchobbens P(2021)On reducing the energy consumption of software product linesProceedings of the 25th ACM International Systems and Software Product Line Conference - Volume A10.1145/3461001.3471142(89-99)Online publication date: 6-Sep-2021
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Pereira RCarção TCouto MCunha JFernandes JSaraiva J(2020)SPELLing out energy leaksJournal of Systems and Software10.1016/j.jss.2019.110463161:COnline publication date: 1-Mar-2020
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Mantel HSchickel JWeber AWeber F(2018)How Secure Is Green IT? The Case of Software-Based Energy Side ChannelsComputer Security10.1007/978-3-319-99073-6_11(218-239)Online publication date: 3-Sep-2018
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Jagroep EBroekman Jvan der Werf JBrinkkemper SLago PBlom Lvan Vliet RFerrario MPernici B(2017)Awakening awareness on energy consumption in software engineeringProceedings of the 39th International Conference on Software Engineering: Software Engineering in Society Track10.1109/ICSE-SEIS.2017.10(76-85)Online publication date: 20-May-2017
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