Cloud-Client Scene Graph UI Rendering Latency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing application deployment methods face challenges in supporting multiple platforms efficiently, leading to latency issues and high development costs due to the complexity of native applications, especially those with high graphical content like user interfaces.
Innovation Solution
A system comprising a cloud application and a client application that uses scene graph data to render user interface elements, where the cloud application generates and transmits presentation and behavior data compatible with the client platform, allowing local rendering on the client device and delegating event processing between the cloud and client applications to reduce latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If stand-alone native applications are deployed on various platforms, then application functionality and business logic can be fully implemented, but development cost increases and platform compatibility becomes difficult
Solution Approach 1:
The application is segmented into two parts: complex business logic and processing tasks are separated and executed on remote servers, while the client device only handles UI rendering and local user interactions. This segmentation allows the application to maintain full functionality through server-side processing while reducing client-side complexity, thereby lowering development costs for multi-platform deployment.
Solution Approach 2:
A scene graph data structure serves as an intermediary between the server and client device. The server generates scene graph data representing the application state and UI elements, which is then transmitted to the client for rendering. This intermediary enables platform-independent application logic while maintaining consistent UI presentation across different devices.
2Shape
If complex applications with high graphical content are deployed on client devices, then user interface quality can be maintained, but device performance becomes constrained and latency increases
Solution Approach 1:
Complex computational tasks and heavy processing requirements are extracted from the client device and relocated to remote servers. The server performs all intensive operations including business logic execution, data processing, and scene graph generation, while the client device only receives pre-processed scene graph data for rendering. This extraction eliminates performance constraints on client devices while maintaining high-quality UI presentation.
3Reliability
If native applications are developed for each platform separately, then platform-specific optimization can be achieved, but development time and cost increase significantly
Solution Approach 1:
The system employs a universal scene graph data format that can represent application state and UI elements in a platform-independent manner. The same server-generated scene graph data can be rendered on any client device regardless of the underlying platform, achieving multi-platform compatibility through a single codebase while maintaining the ability to optimize rendering for specific platforms when needed.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Systems and methods are provided for user interface deployment that include a server with a cloud application and a client device with a client application. The cloud application is a fully functional application, such as a headless application, and transmits scene graph data including presentation data and behavior data for a first set of user interface elements viewable at the client device in a first operational state. The client application locally renders the first set of user interface elements on a client device display to locally render the portion of the scene graph related to the first operational state. In response to a user input, the client application transmits event or state data to the cloud application and may perform an action associated with the user input while awaiting receipt of updated scene graph data, possibly related to a subsequent operational state, reducing or eliminating the perception of latency.