A Genetic Algorithm-Based Approach for Content Delivery in Femtocaching-Assisted Networks

Due to the tremendous and rapid growth of data traffic (e.g. video content), femtocaching has been introduced in 5G networks to bring the data closer to the clients using small, low-power cellular base stations with storage capacity called femtocaches (FCs), hence offloading some traffic off the macrocell base station (MBS). The process of content delivery can efficiently benefit from FCs by optimizing the process of files distribution among the clients using network coding, hence, offloading bandwidth off the MBS and saving costs. In this paper, we propose a genetic algorithm-based approach to minimize the number of orthogonal MBS channels used to distribute files among the clients. Simulation results show that our proposed algorithm almost achieves the optimal solutions found by an exhaustive brute-force search in about 98% of the runs on average. These results significantly make use of the FCs and save the MBS' bandwidth.