Media Transcoding Scheduling Based on Priority
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Solution Overview
Problem
Content delivery networks face inefficiencies in transcoding digital media due to the underutilization of private resources and overutilization of more expensive public resources, as conventional first-in, first-out methods fail to maximize resource usage based on media priority.
Innovation Solution
A method and device that prioritize transcoding digital media based on relative business value by constructing a graph-based representation of incoming demand and available transcoding resources, applying machine learning for optimization, and dynamically scheduling transcoding to allocate resources effectively, ensuring higher-value content is processed first and reducing transcoding errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional first-in, first-out transcoding method is used, then processing order is simple and predictable, but private transcoding resources are underutilized and public resources are overutilized
Solution Approach 1:
The transcoding scheduling system dynamically adjusts processing priorities based on media priority levels and resource availability. High-priority media items are scheduled to use private transcoding resources first, while lower-priority items can utilize public resources, creating a dynamic resource allocation system that adapts to changing conditions rather than following a static FIFO approach.
Solution Approach 2:
The system changes the scheduling parameter from simple arrival-time-based ordering to priority-based ordering. By introducing media priority as a scheduling parameter, the system can differentiate between high-value and low-value content, optimizing resource utilization by directing high-priority items to available private resources and managing public resource usage accordingly.
2Loss of energy
If private transcoding resources are underutilized, then infrastructure costs are reduced, but transcoding throughput and business value delivery are reduced
Solution Approach 1:
The system performs preliminary assessment of media priority and resource availability before scheduling transcoding tasks. By pre-identifying high-priority media items and matching them with available private transcoding resources in advance, the system ensures that private resources are utilized effectively for high-value content, maximizing both resource efficiency and business value delivery.
Solution Approach 2:
The scheduling system automatically matches media items with appropriate transcoding resources based on priority and availability without manual intervention. High-priority items self-select private resources when available, while lower-priority items utilize public resources, creating an efficient self-organizing system that maximizes private resource utilization and reduces overall costs.
3Productivity
If public transcoding resources are overutilized, then transcoding capacity is maintained, but operational costs increase
Solution Approach 1:
The system applies partial utilization of public resources by reserving them as backup capacity rather than relying on them exclusively. Private resources handle the bulk of high-priority transcoding work, while public resources provide supplementary capacity for lower-priority items or overflow demand, avoiding excessive dependence on costly public infrastructure while maintaining adequate transcoding capacity.
Data Source
AI summary
In one example, the present disclosure describes a device, computer-readable medium, and method for transcoding digital media in an optimized manner based on media priority. For instance, in one example, a method includes obtaining a plurality of media content items awaiting transcoding before being distributed over a content distribution network, identifying a plurality of transcoding resources available to transcode the plurality of media items, and generating a schedule for transcoding the plurality of media content items using the plurality of transcoding resources, wherein the schedule prioritizes those media content items of the plurality of media content items that have the highest relative business value.