Latency Compensation in Multiplayer Video Games
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Solution Overview
Problem
Online multiplayer video games suffer from significant degradation in play quality due to latency, which compounds in multiplayer settings, leading to inconsistencies and non-physical object behavior, especially in network environments with varying latency.
Innovation Solution
A latency compensation mechanism that estimates peer player states using behavior models and physics models, refining player-specific models in real-time to mitigate latency effects, allowing for accurate state estimation and improved gameplay coherence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If server synchronization is used to maintain coherence, then logical consistency is maintained, but additional network hops and latency are introduced
Solution Approach 1:
The patent introduces a state estimator as an intermediary component that receives delayed states from the server and generates estimated current states. This estimator acts as a mediator between the server's authoritative (but delayed) state information and the client's need for current state data, allowing the system to maintain logical consistency while reducing the impact of network latency through local prediction and extrapolation
Solution Approach 2:
The system performs preliminary actions by having the client device independently calculate game physics and predict object states in advance, rather than waiting for server confirmation. The state estimator pre-computes likely current states based on delayed server data and local physics simulations, so that when server updates arrive, the client is already prepared with reasonable state estimates, reducing the perceived latency
2Reliability
If artificial time base variation is introduced to maintain logical consistency, then event sequence consistency is maintained, but simulation time base varies and causes non-physical object behavior
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the weighting between server-authoritative states and client-predicted states in the state estimator. Rather than using fixed artificial time base variation, the system modifies the estimation parameters (weights, confidence levels) based on factors like network latency measurements and prediction accuracy, allowing smooth transitions that maintain event consistency while preserving physically accurate object behavior
Solution Approach 2:
The system implements dynamics by making the time base adjustment adaptive rather than static. The state estimator continuously adjusts its predictions based on real-time network conditions and the specific game context, allowing the simulation to dynamically balance between maintaining logical event sequences and preserving physically accurate object behavior without relying on rigid artificial time variations
3Loss of time
If dead reckoning is used to predict future object positions, then prediction is possible with delayed values, but prediction accuracy degrades with large changes in accelerations
Solution Approach 1:
The patent implements feedback by continuously comparing the state estimator's predictions with actual server-provided states and using this information to refine future predictions. The system measures the error between predicted and actual states, then adjusts its prediction model and parameters accordingly, creating a closed-loop system that maintains high prediction accuracy even during periods of large acceleration changes by learning from past prediction errors
Solution Approach 2:
The system changes parameters dynamically by adjusting the prediction model's complexity and weighting based on detected game conditions. When large accelerations are detected, the state estimator modifies its parameters to account for the non-linear motion, switching between different prediction strategies or adjusting the time horizon of predictions to maintain accuracy despite varying motion dynamics
Data Source
AI summary
Latency compensation is performed during play of a multiplayer video game over a network. A first system includes a first estimator, a first player, and a first game object controlled by movement of the first player, and a second system includes at least a second player and a second game object controlled by movement of the second player. The first estimator receives data values characterizing delayed states of the second system via the network. Based on the received data values, the first estimator estimates a latency-compensated state of the second game object using a physics model of the second game object and a behavior model of the second player. The behavior model provides a representation of how the second player interacts with the video game relative to the first player. The first player is enabled to interact with the video game with compensated latency.