An improved Top‐K algorithm for edge servers deployment in smart city

Abstract

AbstractIn smart city IoT applications, the deployment of edge servers has problems such as unbalanced servers load and low servers utilization. Therefore, we study the edge servers deployment problem in mobile edge computing environments for smart cities through an improved Top‐K algorithm in this paper. This algorithm comprehensively considering the distance between base stations and edge servers, the weight ratio of base stations in the base station cluster, the coverage of edge servers, and the upper limit of computing tasks, which aims to reduce the access delay of tasks and deployment cost of edge servers, balance the load among edge servers, improve quality of user experience (QoE), and quality of service (QoS) of the smart city. Firstly, deploy an edge server at the base station with the most tasks and divide base station clusters according to the minimum distance strategy. Then, the location of edge servers adjusted according to the cumulative sum of the weight ratio of base station tasks and distance product in each base station cluster. Finally, the simulation results show that the deployment strategy in this paper is better than other methods in terms of server utilization, load balancing and cost, and is slightly better than other algorithms in terms of delay.