  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.
