Cloud Asset Pipeline for Dynamic Web Link Accuracy
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Solution Overview
Problem
The migration of web assets in cloud-based systems poses challenges in identification and download due to dynamic hosting and re-referencing of assets across different machines, making it difficult to maintain accurate web links and ensure efficient asset retrieval.
Innovation Solution
A method and apparatus that utilize a cyber scraper to seed predetermined URLs, validate them using classification rules, derive predictor values, and generate navigation rules through logistic regression to construct a web asset pipeline, enabling automatic identification and download of web assets or intermediate artifact pages during runtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If web assets are dynamically hosted on different machines in cloud infrastructure, then system flexibility and scalability are improved, but identification and download reliability deteriorate due to re-referencing and migrating web links
Solution Approach 1:
The patent introduces a cloud asset management system as an intermediary between the distributed web assets and users. This system maintains a centralized registry of asset locations, URLs, and metadata, allowing dynamic hosting while preserving reliable access through the intermediary's coordination of asset locations across multiple machines and infrastructure providers
Solution Approach 2:
The system implements feedback mechanisms where the cloud asset management system continuously monitors and updates asset locations, download statuses, and link validity. This feedback loop ensures that even as assets migrate between machines, the system maintains accurate information about current asset locations through continuous verification and updates
2Measurement precision
If manual identification and download methods are used for migrated web assets, then download accuracy may be maintained, but time consumption and operational efficiency deteriorate
Solution Approach 1:
The system enables self-service automated identification and download of web assets through the cloud asset management system. The system automatically tracks asset locations, validates URLs, and executes downloads without manual intervention, maintaining high identification accuracy through automated verification while dramatically reducing retrieval time compared to manual methods
Solution Approach 2:
The cloud asset management system performs preliminary actions by pre-establishing asset registries, validating URLs in advance, and preparing download configurations before actual asset retrieval is needed. This preliminary work ensures accurate identification is already completed and ready, eliminating time delays during actual asset download operations
3Reliability
If comprehensive URL validation and classification rules are implemented, then asset retrieval reliability is improved, but system complexity and processing overhead increase
Solution Approach 1:
The validation system is segmented into modular components: URL validation rules, classification rules, and asset type filters are separated into independent, configurable segments. This modular architecture maintains high reliability through comprehensive validation while reducing overall system complexity by allowing each segment to be independently managed, configured, and optimized without affecting other parts of the system
Data Source
AI summary
Methods, non-transitory computer-readable media, and apparatuses that automate identification and download of one or more web assets residing in a cloud based infrastructure are disclosed. The method may include a training phase and an actual run time phase. In the training phase, the apparatus is trained to identify and download the one or more web assets by generating URLs on its own. The one or more web assets may be an image, document, file containing source code. In the actual run time phase, when the one or more web assets has migrated from one machine to another machine in the cloud, the one or more web assets are again referenced. The apparatus is intelligent enough to detect this re referencing and retrieving the one or web assets.