Empirical comparison of power-efficient virtual machine assignment algorithms

Abstract

The advent of cloud computing has changed the way many companies do computation, allowing them to outsource it to the cloud. This has given origin to a new kind of business, the cloud providers, which run large datacenters. In order to be competitive, cloud providers must keep the energy consumed by the datacenter low. One way to achieve this is with smart task assignment algorithms, which decide where tasks are to be placed upon their arrival. In this paper we compare the performance of multiple task assignment algorithms for saving energy. We assume tasks are in fact virtual machines that have to be assigned to physical machines, and we assume that the physical machines have a power consumption that increases superlinearly with the load. Then, we propose an assignment algorithm VMA2 and compare its performance with other state-of-the-art assignment algorithms, both theoretical or already deployed in real cloud computing platforms. VMA2 leads to low energy consumption. It outperforms the other algorithms in most situations, proving itself to be an effective assignment algorithm for cloud computing platforms.