Hybrid File Compression Model for Container Image Storage
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Solution Overview
Problem
Conventional computing systems face compatibility issues and resource strain when segmenting and compressing container image layers for storage and retrieval, leading to increased system latency and resource usage due to the need for separate checksum operations and system block size considerations.
Innovation Solution
A hybrid multi-function algorithm is used to segment and compress image file layers by creating first and second sets of compression start points for efficient local storage and network access, merging these points to partition the archive file into portions, and generating digests for metadata, allowing for efficient retrieval of missing portions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If conventional segmentation and compression methods are used for container image layers, then storage efficiency is improved, but system latency and resource usage increase due to separate checksum operations and system block size considerations
Solution Approach 1:
The patent combines multiple separate operations (segmentation, compression, and checksum generation) into a single hybrid multi-function algorithm. This merging eliminates the need for separate checksum operations on each segmented file, thereby reducing system latency and resource usage while maintaining storage efficiency through optimized compression.
Solution Approach 2:
The hybrid algorithm serves multiple functions simultaneously: it segments the archive file, compresses the segments, and generates checksums in one unified process. This multi-functionality resolves the contradiction by eliminating the overhead of multiple separate operations while maintaining the benefits of segmentation for storage efficiency.
2Reliability
If separate checksum operations are performed on each segmented file, then data integrity is ensured, but resource strain and system latency increase
Solution Approach 1:
The patent merges the checksum generation operation with the segmentation and compression operations into a single hybrid algorithm. This ensures data integrity through checksums while avoiding the resource strain of performing separate checksum operations on each segmented file.
3Loss of substance
If archive files are segmented for local storage access, then storage efficiency is improved, but compatibility issues arise with system block sizes
Solution Approach 1:
The hybrid algorithm is designed to be system-agnostic, performing segmentation, compression, and checksum generation in a unified manner that does not depend on specific system block sizes. This universality resolves the compatibility issues while maintaining storage efficiency through effective segmentation.
Data Source
AI summary
An archive file that includes an archive start point and an archive end point is received to be segmented and compressed. A first set of compression start points to segment the archive file according to a first function and a second set of compression start points to partition the archive file according to a second function are created. The first set of compression start points and the second set of compression start points are combined to create a set of merged compression start points to partition the archive file into portions between the archive start point and the archive end point. Each portion between the archive start point and the archive end point are compressed to create a compressed archive file.