tp-MA: Orchestrating Three Populations Memetic Algorithm for VNF Deployment in 5G Network.

Virtual network function (VNF) is the key issue and can provide various network services and is widely deployed in 5G communication. Routing and VNF deployment for the VNF service chain (VNF-SC) is a very important and wellknown NP-hard problem. For this problem, if determining the number and locations of data centers is additionally considered, it will be more complexity. In this paper, we investigate a network planning problem by determining all these factors, i.e, by determining not only the optimal routing and the optimal VNF deployment for VNF-SCs, but also the optimal number and locations of data centers. To achieve this purpose, a three objectives optimization model, which minimizes capital expenditure, the maximum index of used frequency slots and the number of deployed VNFs on all data centers, is estimated. To solve this model efficiency, we integrate three objectives into one objective by using a weighted sum strategy. Then, a high-performance memetic algorithm with three populations (tp-MA), which includes well-designed crossover, mutation, and local search operators, is proposed. To demonstrate reasonable of the model and high performance of the designed algorithm, a series of experiments are conducted in several different experimental scenes. Experimental results indicate that the effectiveness of the proposed model and the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]