Paper Info
Title
Seeking for the Optimal Energy Modelisation Accuracy to Allow Efficient Datacenter Optimizations
Abstract
As cloud computing is being more and more used, datacenters play a large role in the overall energy consumption. We propose to tackle this problem, by continuously and autonomously optimizing the cloud datacenters energy efficiency. To this end, modeling the energy consumption for these infrastructures is crucial to drive the optimization process, anticipate the effects of aggressive optimization policies, and to determine precisely the gains brought with the planned optimization. Yet, it is very complex to model with accuracy the energy consumption of a physical device as it depends on several factors. Do we need a detailed and fine-grained energy model to perform good optimizations in the datacenter? Or is a simple and naive energy model good enough to propose viable energy-efficient optimizations? Through experiments, our results show that we don't get energy savings compared to classical bin-packing strategies but there are some gains inusing precise modeling: better utilization of the network and the VM migration processes.
Year
DOI
Venue
2016
10.1109/CCGrid.2016.67
2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)
Keywords
Field
DocType
cloud,placement optimization,energy model
Efficient energy use,Computer science,Server,Real-time computing,Energy consumption,Genetic algorithm,Distributed computing,Virtual machining,Cloud computing
Conference
ISSN
ISBN
Citations 
2376-4414
978-1-5090-2454-4
0
PageRank 
References 
Authors
0.34
7
4
Name
Order
Citations
PageRank
Edouard Outin100.34
jeanemile dartois251.81
Olivier Barais372461.99
Jean-Louis Pazat419928.98