An Edge Server Co-deployment Method via Joint Optimization of Communication Delay and Load Balancing in Edge Collaborative Environment

Abstract

In the edge collaboration environment, the rapid development of smart terminal devices and the huge volume of service requests from smart terminal devices often lead to load imbalance and long communication delay of edge server. In this situation, it's becoming more and more important to efficiently deploy the edge servers to reduce service communication delay and balance the load of edge server, thus fully improving resource utilization of edge server and users' service experience. To this end, this paper proposes a co-deployment method for edge servers in edge collaboration environment by jointly optimizing communication delay and load balancing. It first clusters all communication base stations by the K-means algorithm to derive the most suitable area for edge server deployment. Then, on the premise of balancing the workload between edge servers and minimizing the communication delay between communication base stations and edge servers, the optimal deployment location of edge servers is solved iteratively by the particle swarm algorithm. Finally, validation experiments are conducted based on real data sets of Shanghai Telecom communication base stations, and the experimental results show that the overall performance of the proposed method is better compared with the typical methods such as Top-K, K-means, Random, and Genetic Algorithm.