A Many-objective Optimization Framework for Virtualized Datacenters
Fabio López Pires, Benjamı́n Barán · 2015
The process of selecting which virtual machines should be located (i.e. executed) at each physical machine of a datacenter is commonly known as Virtual Machine Placement (VMP). This work presents a general manyobjective optimization framework that is able to consider as many objective functions as needed when solving the VMP problem in a pure multi-objective context. As an example of utilization of the proposed framework, for the first time a formulation of the many-objective VMP problem (MaVMP) is proposed, considering the simultaneous optimization of the following five objective functions: (1) power consumption, (2) network traffic, (3) economical revenue, (4) quality of service and (5) network load balancing. To solve the formulated many-objective VMP problem, an interactive memetic algorithm is proposed. Simulations prove the correctness of the proposed algorithm and its effectiveness converging to a treatable number of solutions in different experimental scenarios.