Giải thuật di truyền giải bài toán tối ưu đặt và định tuyến trong mạng ảo hóa.

Genetic algorithm for optimizing the Virtual Network Functions Placement and Routing Problem.

Abstract

Recently, the Internet infrastructure is constantly being improved to meet the increasing needs of users. Installing hardware devices in the network server center faces many limitations such as: difficulty in replacing devices; large investment and operating costs,... Network Function Virtualization (NFV) technology was invented to overcome the disadvantages. Specialized hardware will be replaced by software running in visualized environments in this technology. Resource allocation is an important problem in NFV. Reasonable resource allocation can increase service quality and reduce network deployment costs. This research explores the network resource allocation to achieve two objectives: i) reduce deployment costs; ii) reduce the delay of the service chain in the network. We transfer the multi-objective problem to single-objective problem by the weighted-sum approach. Then, this research proposes a mixed-integer linear programming (MILP) model to solve the single-objective optimization problem. The MILP model can provide accurate solutions for small datasets. In order to find solutions for larger sized datasets, the research proposes a genetic algorithm to solve the problem. The experimental results on different datasets demonstrated the effectiveness of the proposed algorithm.