An Edge Server Placement Algorithm based on Genetic Algorithm

With the development of the Internet of Things (IOT) and 5th Generation Mobile Networks (5G), the data traffic generated by edge terminal devices has exploded. Traditional Cloud Computing (CC) technology cannot meet the business requirements of low latency, high efficiency, and high security. Mobile Edge Computing (MEC) has emerged as the times require. The placement of Edge Servers (ES) is a combinatorial optimization problem, and the problem is NP-hard. Faced with the two objectives of delay and efficiency, an ES placement algorithm based on Genetic Algorithm (GA) called EPG is proposed. In order not to increase the dimension of the solution space, the Base Station Request Search Algorithm (BSRSA) is designed to make the GA perform better. In order to avoid the impact of malignant evolution, the traditional GA is optimized, the optimal gene of each iteration is recorded, and the optimal gene in the record is taken as the final Pareto optimal solution. Finally, the EPG was evaluated with the real Shanghai Telecom base station data set.