Container Image Retention Using NFT Priority Scoring
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Solution Overview
Problem
Conventional cloud container storage systems face challenges in managing expanding image repositories, as current storage solutions struggle to scale without experiencing performance bottlenecks, necessitating an efficient storage solution to accommodate continuous influxes of images while ensuring accessibility and scalability.
Innovation Solution
A system that utilizes a non-fungible token (NFT) scoring system to assign priority scores to container images, combined with a concept lattice, to identify which images to retain in the server and archive to a cache memory during system failures, ensuring high-priority images are preserved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional cloud storage solutions are used to accommodate continuous influxes of container images, then storage capacity is improved, but performance bottlenecks occur and scalability deteriorates
Solution Approach 1:
The patent segments container images into two categories: critical images stored in cloud storage and non-critical images stored in local cache. This segmentation allows the system to maintain high storage capacity in the cloud while preserving fast access performance for critical images by keeping them locally available, thus resolving the contradiction between storage capacity and performance.
2Ease of operation
If all container images are retained in the cloud server, then accessibility is improved, but device complexity and management overhead increase during system failures
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing NFT scores for all container images before system failures occur. The NFT scoring engine continuously evaluates images and assigns priority scores, so that when a failure occurs, the system can immediately retrieve high-priority images without complex real-time decision-making, thereby reducing management overhead while maintaining accessibility.
3Reliability
If critical container images are preserved during failures by moving them to local memory, then reliability is improved, but loss of time occurs during the selection and transfer process
Solution Approach 1:
The system performs preliminary action by pre-calculating NFT scores and maintaining a ranked list of critical container images before failures occur. When a failure is detected, the system can immediately transfer the top-ranked images without time-consuming selection processes, thus improving reliability while minimizing time loss.
Solution Approach 2:
The NFT scoring engine operates autonomously to continuously evaluate and rank container images based on their criticality. This self-service mechanism eliminates the need for manual intervention or complex real-time analysis during failures, allowing the system to automatically identify and preserve critical images, thereby improving reliability without significant time loss.
Data Source
AI summary
Embodiments of the invention relate to systems, methods, and computer program products for optimized retention of container images in a cloud server, the invention including: identifying a plurality of container images, where the plurality of container images is stored in the cloud server; generating a non-fungible token (NFT) associated with each container image; using an NFT scoring engine to calculate a score associated with each container image of the plurality of container images; detecting a system failure associated with the cloud server; selecting a first container image of the plurality of container images; and moving the first container image from the cloud server to a local memory device.