  In cloud infrastructure, accommodating multiple virtual networks on a single
physical network reduces power consumed by physical resources and minimizes
cost of operating cloud data centers. However, mapping multiple virtual network
resources to physical network components, called virtual network embedding
(VNE), is known to be NP-hard. With considering energy efficiency, the problem
becomes more complicated. In this paper, we model energy-aware virtual network
embedding, devise metrics for evaluating performance of energy aware virtual
network-embedding algorithms, and propose an energy aware virtual
network-embedding algorithm based on multi-objective particle swarm
optimization augmented with local search to speed up convergence of the
proposed algorithm and improve solutions quality. Performance of the proposed
algorithm is evaluated and compared with existing algorithms using extensive
simulations, which show that the proposed algorithm improves virtual network
embedding by increasing revenue and decreasing energy consumption.
