Rendering Scheduling Framework in Edge Computing: A Congestion Game-based Approach

Mobile gaming has experienced explosive growth in the past few years. Meanwhile, the gaming scenes become more complicated, but the mobile devices have limited computing resources and inadequate energy, which can not satisfy the increasing requirements of mobile games. In recent years, edge computing flourishes as a promising solver to offload computation-intensive tasks to edge devices. However, how to schedule the various rendering tasks to heterogeneous edge servers is challenging because of the variety and unknown workload of the rendering tasks. To overcome these challenges, we design a rendering scheduling framework in edge computing and formulate the rendering scheduling problem as a congestion game, whose objective is to minimize the maximal completion time. We also design a rendering scheduling algorithm based on our congestion game model and derive the Nash Equilibrium and convergence. In addition, we explore a case study called redundant object elimination in rendering scenarios and adopt machine learning tools for workload estimation. Finally, we conduct extensive simulations based on our algorithm, which show significant performance compared with alternative strategies.