A Genetic Algorithm-based Proactive Caching Policy in Edge Networks

Abstract The incredible growth in mobile traffic lays down a challenge to network design. Therefore, proactive caching technology has been proposed as an effective method to reduce network congestion and improve the quality of service. In this paper, we focus on the caching position problem in edge networks and use a mixed integer linear programming (MILP) model to provide the optimal selection. Due to the curse of dimensionality, a genetic algorithm-based caching policy is given to make a balance between performance and time complexity. Numerical investigations reveal that the proposed approach can reduce the total cost by around 20% compared with other widely-used caching methods.