Improving Scalability, Sustainability and Availability via Workload Distribution in Edge-Cloud Gaming

Recent uses of heterogeneous mobile and lightweight devices encourage computations to be abstracted remotely as black box systems. This same concept applies for cloud gaming in which computer games are located and run inside remote rendering servers (RSes). While cloud gaming enables lightweight devices with sufficient input capabilities and network connection to be able to play desktop games, latency and cost issue become significant hindrances in recent applications. In this paper, we came up with our edge-cloud gaming architecture which reduces the overall workload in RSes while increasing playerbase coverage by using edge RSes. Furthermore, we also proposed our allocation algorithm in order to assign incoming players to RSes. From our experiments, our proposed architecture has higher playerbase coverage while our allocation algorithm significantly reduces the cost in both single and batch player arrival pattern.