Quasi Cloud Rendering for Legacy Databases
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Solution Overview
Problem
Current game engines and GPUs struggle to meet requirements for rendering modern graphics with low latency, frame determinism, large traversable areas, non-distracting levels of detail, and multi-channel synchronization while also reducing hardware costs for image generating software, especially in cloud environments.
Innovation Solution
A rendering system comprising a cloud component that preprocesses legacy data into a game-compatible format and a local edge component that performs rendering steps, utilizing a game engine to produce an image stream, with features like data encryption, deterministic frame rate control, and multi-channel synchronization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Weight of stationary object
If cloud services are used to reduce hardware costs, then hardware cost is reduced, but rendering performance and latency may deteriorate
Solution Approach 1:
The rendering system is segmented into cloud-based preprocessing components and edge-based real-time rendering components. The cloud handles data preprocessing and asset generation, while the edge handles time-critical rendering operations, allowing cost reduction through cloud utilization while maintaining low latency through local edge processing.
Solution Approach 2:
Data preprocessing and asset generation are performed in advance on the cloud before real-time rendering is needed. This preliminary action on the cloud allows the edge component to receive preprocessed data ready for immediate rendering, reducing real-time latency while leveraging cloud computing resources.
2Adaptability or versatility
If legacy database formats are used, then compatibility with existing systems is maintained, but integration with modern game engines becomes complex
Solution Approach 1:
An intermediate data processing layer is introduced that acts as a mediator between legacy database formats and modern game engine requirements. This intermediary component handles format conversion and data transformation, maintaining compatibility with legacy systems while providing standardized data structures for modern engines without requiring direct complex integration.
3Manufacturing precision
If high-fidelity graphics rendering is implemented, then visual quality is improved, but hardware requirements and costs increase
Solution Approach 1:
The system uses preprocessed graphical assets and data models generated by cloud-based high-fidelity rendering, which are then copied and reused across multiple edge devices. This allows high-quality graphics to be achieved without each individual device needing expensive hardware, as the rendering workload is distributed to the cloud for asset generation.
4Measurement precision
If deterministic frame rates are enforced, then frame timing precision is improved, but rendering flexibility and adaptability decrease
Solution Approach 1:
The frame rate control system dynamically adjusts between deterministic and flexible modes based on operational requirements. During critical phases where timing precision is essential, the system enforces deterministic frame rates, while during less critical phases, it allows flexible rendering to maintain adaptability and respond to changing conditions.
Data Source
AI summary
A rendering system includes a cloud component and a local edge component. The cloud component receives or retrieves legacy data from various sources and preprocesses the data into a format. The local edge component receives the preprocessed data from the cloud component and performs local rendering steps necessary to place the preprocessed data into a form suitable for a game engine. The game engine utilizes the preprocessed data to render an image stream. The system is embodied in a flight simulator.


