Video Data Processing Resource Allocation Across Locations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Managing video data processing resources becomes cumbersome due to increased storage requirements for higher quality video formats, and determining where to store and process video data efficiently is difficult for users, especially when deciding between local and remote storage.
Innovation Solution
A method that monitors processing requirements and available computing resources at multiple video processing locations to allocate video processing operations efficiently, allowing for dynamic updates and adjustments based on resource availability and user-defined criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video data is stored in higher quality formats to support various applications, then video quality and versatility are improved, but storage space requirements increase and data management becomes more cumbersome
Solution Approach 1:
The patent segments video data into multiple quality versions (different resolutions, frame rates, and quality levels) and stores them in an organized hierarchical structure. This allows the system to provide high-quality video when needed while also maintaining lower-quality versions for casual viewing, thereby supporting format versatility without requiring all users to store all high-quality versions.
Solution Approach 2:
The patent creates and manages multiple copies of video data in different quality formats. Instead of requiring a single high-quality master copy to be accessible everywhere, the system generates derived copies at various quality levels and distributes them appropriately, reducing overall storage requirements while maintaining adaptability to different viewing needs.
2Reliability
If video data is distributed between local and remote storage to improve accessibility and backup capabilities, then data availability and security are improved, but determining optimal storage location becomes more difficult
Solution Approach 1:
The patent implements automated policies that enable the system to self-manage video data distribution between local and remote storage. The system automatically determines optimal storage locations, transfers data between locations, and manages local versus remote copies based on predefined criteria such as data access patterns, storage capacity, and user preferences, eliminating the need for manual intervention.
Solution Approach 2:
The patent incorporates monitoring and feedback mechanisms that track video data access patterns, storage resource availability, and system performance. Based on this feedback, the system dynamically adjusts storage and processing operations, automatically optimizing the distribution of video data between local and remote locations without requiring manual configuration or user decision-making.
3Speed
If video processing operations are performed locally to reduce latency and improve real-time processing, then processing speed is improved, but local computing resource requirements increase
Solution Approach 1:
The patent implements local quality processing where each location (local device or remote server) performs processing operations appropriate to its capabilities and the specific needs of the video data. Critical real-time processing operations that require low latency are performed locally, while less time-sensitive operations are deferred to remote locations with greater computing resources, optimizing both speed and resource utilization.
4Device complexity
If more video processing operations are allocated to a single location to simplify management, then operational complexity is reduced, but resource bottlenecks and single points of failure increase
Solution Approach 1:
The patent segments video processing operations across multiple locations rather than concentrating them at a single point. Different processing tasks are distributed to local devices and remote servers based on their capabilities and current resource availability, creating a resilient distributed processing architecture that avoids single points of failure while maintaining manageable operational complexity through automated coordination.
Data Source
AI summary
Systems, methods, and software described herein manage video data processing resources for video data obtained from one or more sources. In one implementation, a management system may monitor processing requirements for the video data and computing resources available at multiple video processing locations. The management system may further allocate processing operations to the video processing locations based on the processing requirements for the video data and computing resources available at the video processing locations.


