Cross-Layer Optimization for State Update in Mobile Gaming

In a large-scale mobile gaming environment with limited wireless network bandwidth, efficient mechanisms for state update are crucial to allow graceful real-time interaction for a large number of players. By using the state updating threshold as a key parameter that bridges the resulting state distortion and the network traffic, we are able to study the fundamental traffic-distortion tradeoffs via both theoretical modeling and numerical analysis using real game traces. We consider a WiMAX link model, where the bandwidth allocation is driven by the underlying physical layer link quality as well as application layer gaming behaviors. Such a cross-layer optimization problem can be solved using standard convex programming techniques. By exploring the temporal locality of gaming behavior, we also propose a prediction method for on-line bandwidth adaptation. Using real data traces from a multiplayer driving game, TORCS, the proposed network-aware bandwidth allocation method (NABA) is able to achieve significant reduction in state distortion compared to two baselines: uniform and proportional policies.