Energy-Aware Resource Allocation

Damien Borgetto (1) , Georges da Costa (1) , Jean-Marc Pierson (1) , Amal Sayah (1)

1 IRIT-SEPIA - Système d’exploitation, systèmes répartis, de l’intergiciel à l’architecture

This paper deals with the reduction of energy consumption in large scale systems, especially by taking into account the impact of energy consumption for server consolidation. Decreasing the number of physical hosts used while ensuring a certain level of quality of services is the goal of our approach. We introduce a metric called energetic yield which represents the quality of a task placement on a subset of machines, while taking into account quality of service and energy efficiency aspects. It measures the difference between resources required by a job and what the system allocates ultimately, while trying to save energy. Our work aims at minimizing this difference. We propose placement heuristics that are compared to the optimal solution and to a related system. In this paper, we present a set of experiments showing the relevance of this metric in order to reduce significantly energy consumption.

Keywords: Resource management; Energy consumption; Quality of service; Energy efficiency; Hardware; Physics computing; Large-scale systems; Energy measurement; Europe; Cooling

Domains: Distributed, Parallel, and Cluster Computing [cs.DC]

Damien Borgetto, Georges da Costa, Jean-Marc Pierson, Amal Sayah. Energy-Aware Resource Allocation. Energy Efficient Grids, Clouds and Clusters Workshop (co-located with Grid 2009) (E2GC2 2009), Oct 2009, Banff, Canada. ⟨10.1109/GRID.2009.5353063⟩. ⟨hal-00684523⟩