Empirical comparison of power-efficient virtual machine assignment algorithms

In this paper we compare the performance of multiple task assignment algorithms for saving energy. We assume that 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. First, we propose two tunable power-aware task assignment algorithms (that subsume the algorithms studied in Arjona et al., Power-efficient assignment of virtual machines to physical machines, Future Generation Computer Systems, 2015). These algorithms are then compared with multiple state-of-the-art algorithms in different meaningful scenarios. Both algorithms prove themselves as interesting assignment algorithms since, properly configured, they outperform the other algorithms in most of the cases.