Cloud-Based File And Object Archiving With Cost Simulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Organizations face challenges in efficiently managing and protecting increasing volumes of data while minimizing costs and maintaining compliance with retention objectives, as existing data archiving solutions often lack interoperability and are not scalable.
Innovation Solution
A data storage management system that implements software-as-a-service (SaaS) solutions for cloud-based archiving, enabling users to model and simulate archiving plans, apply multiple archiving criteria independently, and perform granular data selection and archiving based on metadata and content analysis, with graphical visualization of outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is archived to cloud storage repositories, then storage costs are reduced and primary storage space is freed up, but data accessibility and retrieval time increase
Solution Approach 1:
The system creates index structures and metadata records before data is archived to cloud storage. This preliminary indexing action enables rapid data location and retrieval without requiring full scanning of archived data, thus reducing retrieval time while maintaining cost-effective cloud storage architecture
Solution Approach 2:
The patent introduces an intermediary indexing layer between primary storage and cloud archive storage. This intermediary structure stores metadata and index information that facilitates quick data location in the archive, bridging the gap between fast primary storage access and cost-effective cloud storage
2Manufacturing precision
If granular data selection and archiving is implemented based on metadata and content analysis, then archiving precision is improved, but system complexity and processing time increase
Solution Approach 1:
The system segments data archiving into distinct layers: metadata analysis, content analysis, and archiving execution. Each layer handles specific tasks independently, allowing granular control over what gets archived while managing system complexity through modular design
Solution Approach 2:
The patent applies partial action by selectively archiving only specific portions of data that meet defined criteria, rather than archiving entire datasets. Content analysis and metadata filtering enable precise identification of archivable data segments, improving archiving precision without processing unnecessary data
3Adaptability or versatility
If multiple archiving plans are implemented with different criteria, then archiving versatility is improved, but management complexity and computational overhead increase
Solution Approach 1:
The system implements a universal archiving platform that supports multiple archiving plans with different criteria through a common framework. The same infrastructure handles various archiving strategies, reducing management complexity while maintaining high versatility through configurable policies
Solution Approach 2:
The patent introduces dynamic policy selection that automatically chooses appropriate archiving plans based on data characteristics, current system state, and predefined rules. This dynamic approach manages multiple archiving plans without requiring manual intervention, reducing management complexity while preserving versatility
Data Source
AI summary
The disclosed data storage management system enables data owners to model the costs and attributes of archiving their data and to readily capture and implement one or more resultant archiving plans. Modeling enables data owners to make informed choices about cost profiles before data is actually archived. Archiving plans devised according to these choices are intended to save on data storage costs and provide a compliance-ready data archive in cloud storage repository(ies). Armed with archiving simulations supplied by the illustrative data storage management system, a data owner may control data placement to predict costs, free up primary storage, and move inactive data to less expensive archive storage. Preferably, the disclosed system is implemented as a software-as-a-service (Saas) solution, and the accompanying archive storage is implemented as a cloud storage service, but the invention is not limited to SaaS or to cloud-based data archives.