@conference {, title = {Process-level Power Estimation in VM-based Systems}, booktitle = {EuroSYS}, year = {2015}, publisher = {ACM}, organization = {ACM}, address = {Bordeaux, France}, abstract = {
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 middleware
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.
}, doi = {http://dx.doi.org/10.1145/2741948.2741971}, author = {Maxime Colmant and Mascha Kurpicz and Felber, Pascal and Loic Huertas and Romain Rouvoy and Sobe, Anita} }