Split Lightfield Rendering via Proxy Edge-Cloud Task Partitioning
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Solution Overview
Problem
Existing immersive media technologies face challenges in rendering high-quality lightfield content on devices with limited processing power, as they require significant local computational resources that many devices cannot provide.
Innovation Solution
A proxy-edge-cloud architecture is employed to split rendering tasks between edge computing and cloud computing systems, with a rendering proxy transcoding scenes to reduce local processing demands, allowing devices with lower capabilities to stream immersive media effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If immersive media rendering is performed locally on end devices, then rendering quality can be maintained, but device processing power requirements become excessively high
Solution Approach 1:
A rendering proxy server is introduced as an intermediary component between the end device and the edge/cloud computing systems. The proxy server manages rendering task distribution, handles device capability assessment, and coordinates with multiple edge and cloud rendering systems to deliver high-quality immersive media content to devices with limited processing power
Solution Approach 2:
The rendering system is segmented into multiple independent components: edge computing systems for latency-sensitive tasks, cloud computing systems for computationally intensive tasks, and a proxy server for coordination. This segmentation allows different types of processing to be distributed across appropriate infrastructure, maintaining quality while reducing local device requirements
2Ease of operation
If rendering tasks are offloaded to cloud computing systems, then local processing demands are reduced, but network latency and processing delays increase
Solution Approach 1:
Different parts of the rendering pipeline are assigned to different computing locations based on their specific requirements: edge computing systems handle tasks requiring low latency (such as real-time rendering), while cloud computing systems handle less time-sensitive computationally intensive tasks (such as pre-processing and post-processing). This local quality approach optimizes the balance between processing demand and latency
Solution Approach 2:
The system dynamically selects and switches between edge and cloud computing systems based on real-time conditions including network status, device capabilities, and task requirements. This dynamic adaptation allows the system to optimize performance by choosing the most appropriate computing resource for each specific rendering task
3Productivity
If a proxy server dynamically groups rendering tasks between edge and cloud systems, then task distribution efficiency improves, but system complexity increases
Solution Approach 1:
The proxy server is designed as a universal coordination component that handles multiple functions: device capability assessment, task prioritization, edge and cloud system management, and result composition. By consolidating these diverse functions into a single multi-functional proxy server, the system manages complexity centrally rather than distributing it across multiple components
Data Source
AI summary
A system and method for split rendering immersive media using proxy edge cloud computing architecture. The system and method may include dynamically determining a task-split or splitting a task for rendering a scene in an immersive media stream into two or more computational tasks based on one or more processing delays, wherein the task-splitting splits the scene into first part including one or more first tasks performed by an edge computing system and second part including one or more second tasks performed by a cloud computing system. The system and method may include transmitting the first parts of the scene, and transmitting the second parts of the scene.