Title :

Process-level Power Estimation in VM-based Systems

Author(s) :

Colmant, Maxime [Auteur]
Université de Lille, Sciences et Technologies
Agence de l'Environnement et de la Maîtrise de l'Énergie [ADEME]
Self-adaptation for distributed services and large software systems [SPIRALS]
Kurpicz, Mascha [Auteur]
Institut d'Informatique [Neuchâtel] [IIUN]
Université de Neuchâtel = University of Neuchatel [UNINE]
Felber, Pascal [Auteur]
Institut d'Informatique [Neuchâtel] [IIUN]
Université de Neuchâtel = University of Neuchatel [UNINE]
Huertas, Loïc [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Université de Lille, Sciences et Technologies
Rouvoy, Romain [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Université de Lille, Sciences et Technologies
Sobe, Anita [Auteur]
Institut d'Informatique [Neuchâtel] [IIUN]
Université de Neuchâtel = University of Neuchatel [UNINE]

Scientific editor(s) :

Tim Harris and Maurice Herlihy

Conference title :

European Conference on Computer Systems (EuroSys)

City :

Bordeaux

Country :

France

Start date of the conference :

2015-04-21

Journal title :

EuroSys'15: Proceedings of the Tenth European Conference on Computer Systems

Publisher :

ACM

Publication date :

2015-04-21

English keyword(s) :

Virtual Environment
Middleware toolkit
Operating system
Power Consumption

HAL domain(s) :

Informatique [cs]/Génie logiciel [cs.SE]
Informatique [cs]/Système d'exploitation [cs.OS]
Informatique [cs]/Informatique ubiquitaire
Informatique [cs]/Informatique mobile
Informatique [cs]/Web
Informatique [cs]/Recherche d'information [cs.IR]

English abstract : [en]

Power estimation of software processes provides critical indicators to drive scheduling or power capping heuristics. State-of-the-art solutions can perform coarse-grained power estimation in virtualized environments, ...
Show more >Power estimation of software processes provides critical indicators to drive scheduling or power capping heuristics. State-of-the-art solutions can perform coarse-grained power estimation in virtualized environments, typically treating virtual machines (VMs) as a black box. Yet, VM-based systems are nowadays commonly used to host multiple applications for cost savings and better use of energy by sharing common resources and assets.In this paper, we propose a fine-grained monitoring mid- dleware providing real-time and accurate power estimation of software processes running at any level of virtualization in a system. In particular, our solution automatically learns an application-agnostic power model, which can be used to estimate the power consumption of applications.Our middleware implementation, named BitWatts, builds on a distributed actor implementation to collect process usage and infer fine-grained power consumption without imposing any hardware investment (e.g., power meters). BitWatts instances use high-throughput communication channels to spread the power consumption across the VM levels and between machines. Our experiments, based on CPU- and memory-intensive benchmarks running on different hardware setups, demonstrate that BitWatts scales both in number of monitored processes and virtualization levels. This non-invasive monitoring solution therefore paves the way for scalable energy accounting that takes into account the dynamic nature of virtualized environments.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 :

Harvested from HAL