Meet Genetic Algorithms in Monte Carlo: Optimised Placement of Multi-Service Applications in the Fog

Managing multi-service applications on top of dynamic and heterogeneous Fog infrastructures is intrinsically challenging and requires suitable tooling to support decision-making. Indeed, bad service deployment decisions can lead to unsatisfactory application QoS, to waste of computing resources or money, and to application downtime. In this paper, we illustrate how combining Genetic Algorithms with Monte Carlo simulations can considerably improve the efficiency of exhaustively searching for QoS-aware application deployments.