Meet Genetic Algorithms in Monte Carlo: Optimised Placement of Multi-Service Applications in the Fog
Antonio Brogi, Stefano Forti, Carlos Guerrero, Isaac Lera · 2019
Managing multi-service applications on top of dynamic and heterogeneous Fog infrastructures is intrinsically challenging and requires suitable tooling to support decisionmaking. 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.