Lossless Data Rendition Storage for Cloud Efficiency
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Solution Overview
Problem
Cloud service providers face escalating costs and increased computational demands due to the need to maintain multiple copies of data and provide data in various formats, as users increasingly expect access to data in different forms and formats beyond its original storage form.
Innovation Solution
Storing alternate renditions of user data through lossless transformations, such as compression or schema changes, allows for efficient delivery of data in various formats without the need for complex computations, reducing storage requirements and computational overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple copies of data are maintained to ensure reliability and provide various formats, then user access flexibility and reliability are improved, but storage costs and computational demands increase
Solution Approach 1:
The patent applies the copying principle by creating alternate renditions of data through lossless transformations. Instead of storing multiple complete copies of data in different formats, the system stores transformed versions (copies) that can be efficiently converted back to the original format. This allows the system to provide data in various formats while using less storage space than maintaining multiple full copies.
Solution Approach 2:
The patent applies parameter changes by transforming data using lossless transformations that alter the representation parameters of the data. These transformations change how data is encoded or structured (parameters) while preserving the ability to reconstruct the original data. This enables format flexibility through parameter transformation rather than storing multiple format variants.
2Reliability
If multiple copies of data are maintained to ensure reliability, then data availability is improved, but storage costs increase
Solution Approach 1:
The system creates alternate renditions as transformed copies of the original data. These copies store the essential information in a different representation that can be used to reconstruct the original data, providing redundancy and reliability while occupying less storage space than full copies.
Solution Approach 2:
The system performs lossless transformations in advance to create alternate renditions before they are needed. This preliminary action prepares multiple representational forms of the data upfront, ensuring reliability and availability when requested, while the transformed nature of these pre-prepared copies reduces the storage space required compared to storing full redundant copies.
3Quantity of substance
If data is stored in original format only, then storage space is minimized, but computational demands increase when format conversion is needed
Solution Approach 1:
The system performs lossless transformations in advance to create alternate renditions of data in different formats. By preparing these transformed versions beforehand and storing them, the system avoids the need to perform computationally intensive format conversions in real-time when users request data in different formats, thus reducing the computational power required during data access operations.
4Quantity of substance
If alternate renditions are stored instead of original data, then storage capacity is reduced, but the ability to restore original data must be maintained
Solution Approach 1:
The system creates alternate renditions as transformed copies that preserve the essential information content of the original data. These copies are generated through lossless transformations, meaning they contain all the necessary information to reconstruct the original data exactly, thus maintaining data restoration capability while using less storage capacity than the original format.
Solution Approach 2:
The system applies lossless transformations that change the parameters of data representation while preserving the underlying information. These parameter changes alter how data is encoded or structured in the alternate renditions, reducing storage requirements, but the transformation is designed to be reversible, ensuring that the original data can be fully restored when needed.
Data Source
AI summary
Techniques and environments that increase the convenience, efficiency and variety of cloud services are offered to clients. User data having an original representational format is losslessly transformed to form one or more alternate renditions having various representational formats based on the lossless transforms. The renditions, which may be pre-generated, can be stored on a network server instead of the identical user data to thereby reduce redundant computation and storage costs. In some cases both the renditions and the original use data may be stored. The original user data may be reconstructed, recreated, or restored using the alternate renditions.