Software-Defined Media Platform Dynamic Resource Allocation
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Solution Overview
Problem
Current media delivery platforms are inflexible and inefficient in resource allocation, leading to high costs due to over-provisioning during peak times and underutilization during low-demand periods, as they cannot easily adapt to variations in demand or resource availability without disrupting consumer viewing sessions.
Innovation Solution
A software-defined media platform with dynamic resource allocation capabilities, utilizing distributed computer hardware and software modules for transcoding and packaging media streams, allowing for real-time adjustment of bitrates and processing resources based on demand, user analytics, and other parameters, enabling efficient use of resources across multiple access technologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple versions of media streams are provisioned for all channels to support all access technologies, then user experience quality is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The system dynamically adjusts the number of media stream versions and processing resources based on real-time demand metrics. During peak times, additional bitrates and processing resources are automatically added; during low-demand periods, resources are reduced. This dynamic allocation allows the system to maintain high user experience quality when needed while avoiding resource waste during off-peak times.
Solution Approach 2:
The system changes operational parameters such as the number of concurrent transcoding operations, bitrate variations, and processing throughput based on demand conditions. By adjusting these parameters dynamically rather than maintaining fixed high-capacity provisioning, the system achieves both high reliability during peak usage and improved resource efficiency during lower demand periods.
2Reliability
If processing resources are allocated in advance for all channels, then service reliability is improved, but adaptability to demand variations deteriorates
Solution Approach 1:
The system transitions from static advance allocation to dynamic allocation where resource provisioning automatically adjusts to actual demand. The platform monitors usage patterns and demand metrics in real-time, enabling it to adapt resource allocation to varying conditions while maintaining service reliability through automated scaling capabilities.
Solution Approach 2:
The system implements feedback mechanisms that monitor demand conditions, user analytics, and resource utilization metrics. This feedback information is used to automatically adjust resource allocation decisions, allowing the system to adapt to demand variations while maintaining service reliability through continuous optimization based on actual system state.
3Productivity
If resources are increased for premium channels to handle large audiences, then service capacity is improved, but resource allocation efficiency deteriorates
Solution Approach 1:
The system applies different resource allocation strategies to different channels based on their specific characteristics and demand patterns. Premium channels with large audiences receive increased resources when needed, while standard or low-volume channels receive minimal resources. This localized, channel-specific resource allocation optimizes both service capacity for premium content and overall resource allocation efficiency.
Solution Approach 2:
The system dynamically changes resource allocation parameters for different channels based on their performance requirements and actual usage. Premium channels can have their bitrate, resolution, and processing resources adjusted independently from other channels, allowing the system to maximize service capacity where needed while minimizing waste on channels with lower demand.
Data Source
AI summary
A software-defined media platform having one or more media processing units that may be dynamically instantiated, interconnected and configured according to changes in demand, resource availability, and other parameters affecting system performance relative to demand. In one example media processing method, a source media stream may be received via multicast or unicast. The source media stream may be processed into one or more levels of work product segments having different media characteristics by a plurality of transcoding processing units, as needed. One or more levels of work product segments, or the source media stream, may be packaged (e.g., including resegmenting) into final work product segments having select media characteristics, which may be uploaded to a cloud storage unit for delivery to end users.