IARA: An Orchestrating Improved Artificial Raindrop Algorithm for VNFs Deployment in Network Function Virtualization

摘要

Network Function Virtualization (NFV) can provide the resource according to the request and can improve the flexibility of the network. It has become the key technology of 5G communication. Resource scheduling for virtual network function service chain (VNF-SC) is the key issue of the NFV. In this paper, the problem of routing and VNFs deployment for VNF service chain (VNF-SC) in inter-data center elastic optical networks (inter-DC EONs) is investigated. We investigate the inter-DC EONs that each data center only can provide some specific VNFs, and the system resources of all the data centers are limited. In addition, part of requiblack VNFs in each VNF-SC is dependent, i.e., the relative order of requiblack VNFs is fixed. To solve the challenging problem, we first establish a mix-integer programming model. Then, to make the population distributed on the search domain uniformly, uniform design method was developed. In addition, an improved artificial raindrop algorithm (IARA) for the established model, which inspired by particle swarm optimization and differential evolution, is proposed to solve the maximum model efficiently. Finally, to demonstrate high performance of the designed algorithm, a series of experiments are conducted in several different experimental scenes. Experimental results indicate that the proposed algorithm can obtain the better results than compared algorithm.