Hierarchical Data Storage for DVRs
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Solution Overview
Problem
Digital video recorders (DVRs) face challenges in efficiently managing storage space for high-quality video data, often requiring costly solutions like large disk drives or reducing video quality, which can compromise data integrity for analysis.
Innovation Solution
A method and system that encode input data into multiple streams, allowing for high-quality representation and separate recording, enabling storage of high-quality data while reducing storage requirements by deleting lower-quality streams when no longer needed, using a hierarchical data structure that allows for flexible quality levels and efficient storage management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If more storage space is provided by installing large disk drives, then storage capacity is improved, but cost increases
Solution Approach 1:
The video stream is segmented into multiple quality levels (base layer and enhancement layers) that are recorded separately. This allows the system to store high-quality video when needed while using lower-quality recordings for routine storage, effectively segmenting the storage requirement over time and quality levels.
Solution Approach 2:
The system dynamically adjusts recording quality based on storage needs and event importance. High-quality recording is applied selectively to events of interest while routine recording uses lower quality, allowing the system to adapt storage consumption to actual operational requirements rather than maintaining constant high-quality recording.
2Quantity of substance
If data quality is reduced by using lower resolution or higher compression, then storage space is improved, but data quality deteriorates
Solution Approach 1:
The video stream is divided into a base layer and enhancement layers with different quality characteristics. The base layer provides acceptable quality for routine viewing while enhancement layers add detail for critical events, allowing segmentation of quality requirements over time.
Solution Approach 2:
The system performs preliminary recording at multiple quality levels simultaneously, preparing both base and enhancement layers in advance. This allows the system to have high-quality data ready for critical events while using lower-quality data for routine storage needs.
3Reliability
If continuous high-quality recording is performed, then data availability is improved, but storage capacity is consumed faster
Solution Approach 1:
The recording system segments data into multiple quality tiers that can be managed differently over time. Critical events are marked and retained at high quality while routine footage is managed at lower quality, segmenting the storage consumption pattern to sustain longer retention periods.
Solution Approach 2:
The system changes recording parameters (quality level, compression ratio) dynamically based on event detection and storage requirements. When an event is detected, the system switches to high-quality recording parameters; during routine operation, it uses lower-quality parameters to extend retention time.
4Quantity of substance
If recording is performed selectively at significant times, then storage capacity is improved, but data completeness deteriorates
Solution Approach 1:
The system performs preliminary recording of events at high quality before the actual event occurs, capturing context and leading events. This preliminary action ensures that when an event is detected, the system already has high-quality data ready, eliminating the need to choose between storage capacity and data completeness.
Data Source
AI summary
A method and system for encoding and recording data in a multi-stream format when the data is initially captured. The multiple streams of data can be combined to provide a high quality, or high resolution, representation, while a reduced subset of the streams can provide a lower quality, or lower resolution, representation. Data storage requirements can be reduced, by deleting one or more of the streams, when there is no longer a need for retention of the data at the higher quality.