Honolulu, HI, USA USA
June 24, 2012 to June 29, 2012
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CLOUD.2012.50
Energy efficiency has now become one of the major design constraints for current and future cloud data center operators. One way to conserve energy is to transition idle servers into a lower power-state (e.g. suspend). Therefore, virtual machine (VM) placement and dynamic VM scheduling algorithms are proposed to facilitate the creation of idle times. However, these algorithms are rarely integrated in a holistic approach and experimentally evaluated in a realistic environment. In this paper we present the energy management algorithms and mechanisms of a novel holistic energy-aware VM management framework for private clouds called Snooze. We conduct an extensive evaluation of the energy and performance implications of our system on 34 power-metered machines of the Grid'5000 experimentation testbed under dynamic web workloads. The results show that the energy saving mechanisms allow Snooze to dynamically scale data center energy consumption proportionally to the load, thus achieving substantial energy savings with only limited impact on application performance.
Resource management, Vectors, Monitoring, Heuristic algorithms, Energy management, Servers, Estimation, Virtualization, Cloud Computing, Energy Management, Consolidation, Relocation, Live Migration
Eugen Feller, Cyril Rohr, David Margery, Christine Morin, "Energy Management in IaaS Clouds: A Holistic Approach", CLOUD, 2012, 2013 IEEE Sixth International Conference on Cloud Computing, 2013 IEEE Sixth International Conference on Cloud Computing 2012, pp. 204-212, doi:10.1109/CLOUD.2012.50