Propagation Dynamics Based Resource Deployment Strategy for Edge Networks
Shaoshuai Fan, Hanlin Gao, Hui Tian, Shiyu Yang · 2023
In mobile edge network, dynamically changing content requests can affect network resource deployment. In recent years, epidemic model has been explored to describe the dynamic content popularity. In this article, epidemic model is applied to characterize the content propagation in resource-limited edge networks. The epidemic parameters are analyzed through the data collected by network entities. In order to maximize satisfaction rate of users, we decompose the joint optimization problem and propose a base station caching placement and resource allocation algorithm based on propagation dynamics. Simulation results verify that the proposed strategy offers higher satisfaction rate compared with other benchmark algorithms.