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Monitoring Energy Hotspots in Software
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Document type :
Article dans une revue scientifique
DOI :
10.1007/s10515-014-0171-1
Title :
Monitoring Energy Hotspots in Software
Author(s) :
Noureddine, Adel [Auteur]
Université de Lille, Sciences et Technologies
Self-adaptation for distributed services and large software systems [SPIRALS]
Rouvoy, Romain [Auteur] refId
Self-adaptation for distributed services and large software systems [SPIRALS]
Université de Lille, Sciences et Technologies
Seinturier, Lionel [Auteur] refId
Self-adaptation for distributed services and large software systems [SPIRALS]
Université de Lille, Sciences et Technologies
Institut Universitaire de France [IUF]
Journal title :
Automated Software Engineering
Pages :
291-332
Publisher :
Springer Verlag
Publication date :
2015-09
ISSN :
0928-8910
English keyword(s) :
Power Model
Power Monitoring
Energy Consumption
HAL domain(s) :
Informatique [cs]/Génie logiciel [cs.SE]
Informatique [cs]/Recherche d'information [cs.IR]
English abstract : [en]
Green IT has emerged as a discipline concerned with the optimiza- tion of software solutions with regards to their energy consumption. In this domain, most of the state-of-the-art solutions concentrate on coarse-grained ...
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Green IT has emerged as a discipline concerned with the optimiza- tion 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 2-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.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Source :
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