A bi-level model and evolution algorithm for virtual network functions deployment in inter-datacenter elastic optical networks

Abstract The technology of network function virtualization can effectively reduce the cost of network investment, its key problem is the deployment of virtual network functions, these are transmitted by some data centers. An new model of bi-level optimization is established in this paper, and a hybrid algorithm is proposed by combining a distributed estimation algorithm and differential evolution. Firstly, according to the characteristics of the upper-level variables, the upper-level objectives are optimized by using a binaryencoded distribution estimation algorithm; Then, the differential evolution is used to solve the lower-level problem, and a correlation coefficient is used to select individuals in the design of mutation operator, and in the operation some high-quality individuals are embedded to produce mutation offspring, the search efficiency of the algorithm can be improved in this process. The experimental results on two realworld examples show that the proposed algorithm provides a better deployment scheme.