Title :
Energy Efficient Virtual Machine Consolidation under Uncertain Input Parameters for Green Data Centers
Author :
Enrica Zola;Andreas J. Kassler
Author_Institution :
Dept. of Network Eng., UPC, Barcelona, Spain
Abstract :
Reducing the energy consumption of data centers and the Cloud is very important in order to lower CO_2 footprint and operational cost (OPEX) of a Cloud operator. To this extent, it becomes crucial to minimise the energy consumption by consolidating the number of powered-on physical servers that host the given virtual machines (VMs). In this work, we propose a novel approach to the energy efficient VM consolidation problem by applying Robust Optimisation Theory. We develop a mathematical model as a robust Mixed Integer Linear Program under the assumption that the input to the problem (e.g. resource demands of the VMs) is not known precisely, but varies within given bounds. A numerical evaluation shows that our model allows the Cloud Operator to tradeoff between the power consumption and the protection from more severe and unlikely deviations of the uncertain input.
Keywords :
"Power demand","Robustness","Uncertainty","Energy consumption","Optimization","Data models","Cloud computing"
Conference_Titel :
Cloud Computing Technology and Science (CloudCom), 2015 IEEE 7th International Conference on
DOI :
10.1109/CloudCom.2015.15