Abstract:
Data centres are facilities with large amount of machines
(i.e., servers) and hosted processes (e.g., virtual machines). Managers of
data centres (e.g., operators, capital allocators, CRM) constantly try to
optimise them, reassigning `better' machines to processes. These man-
agers usually see better/good placements as a combination of distinct
objectives, hence why in this paper we de ne the data centre optimisa-
tion problem as a multi-objective machine reassignment problem. While
classical solutions to address this either do not nd many solutions (e.g.,
GRASP), do not cover well the search space (e.g., PLS), or even can-
not operate properly (e.g., NSGA-II lacks a good initial population), we
propose GeNePi, a novel hybrid algorithm. We show that GeNePi out-
performs all the other algorithms in terms of quantity of solutions (nearly
6 times more solutions on average than the second best algorithm) and
quality (hypervolume of the Pareto frontier is 106% better on average).