A Genetic Algorithm-based approach for placement in the fog of latency-sensitive multiplayer game servers

First-Person Shooter (FPS) games are among the most popular latency-sensitive multiplayer online games. A separate game server manages each multiplayer group hosted appropriately to meet the given Quality of Service (QoS) and Quality of Experience (QoE) requirements of the game and the players. Cloud computing is typically used to host these game servers to cope with changing workload requirements, given its elasticity, scalability, and on-demand provisioning characteristics [1]. However, the Cloud still suffers from known latency limitations, especially when dealing with latency-sensitive applications such as FPS games. Hence, Fog computing can be a good alternative for hosting FPS game servers, given that Fog nodes hosting the servers can be placed close to the players, thereby reducing latency. However, a careful resource management is necessary given the Fog's capacity unpredictability. This paper introduces an optimization-based game server placement approach that minimizes server costs while optimizing latency delays and, eventually, QoE for the players. A static model for the server placement problem is formulated as an Integer Linear Program (ILP) with valid inequalities. Given the complexity of the problem, a resolution strategy based on a non-linear, double penalty relaxation technique in conjunction with a proven Genetic Algorithm (GA) is developed. A dynamic version of the placement problem is also formulated to cope with the realistic scenarios dealing with changing multiplayer groups and Fog servers. A two-step dynamic scheme, based on the developed GA, is applied. Extensive simulations are conducted showing a good performance of the proposed approach both in terms of solution quality and execution time.