A decentralized optimization policy for service placement in fog computing is presented. The optimization is addressed to place most popular services as closer to the users as possible. The experimental validation is done in the iFogSim simulator and by comparing our algorithm with the simulator's built-in policy. The simulation is characterized by modeling a microservice-based application for different experiment sizes. Results showed that our decentralized algorithm places most popular services closer to users, improving network usage and service latency of the most requested applications, at the expense of a latency increment for the less requested services and a greater number of service migrations.

翻译：提出了一种面向雾计算服务部署的去中心化优化策略。该优化旨在将最受欢迎的服务尽可能部署在靠近用户的位置。实验验证在iFogSim模拟器中进行，并通过将我们的算法与该模拟器内置策略进行对比。仿真过程以不同实验规模下基于微服务的应用程序为建模特征。结果表明，我们的去中心化算法能将最受欢迎的服务部署至更靠近用户的位置，从而改善网络利用率及最常请求应用程序的服务延迟，但代价是低频请求服务的延迟增加及服务迁移次数增多。